Overview

Brought to you by YData

Dataset statistics

Number of variables152
Number of observations67821
Missing cells3253857
Missing cells (%)31.6%
Total size in memory79.2 MiB
Average record size in memory1.2 KiB

Variable types

Numeric108
Unsupported1
Categorical24
Text5
DateTime11
Boolean3

Alerts

policy_code has constant value "1.0" Constant
hardship_type has constant value "INTEREST ONLY-3 MONTHS DEFERRAL" Constant
deferral_term has constant value "3.0" Constant
hardship_length has constant value "3.0" Constant
acc_now_delinq is highly overall correlated with delinq_amnt and 4 other fieldsHigh correlation
acc_open_past_24mths is highly overall correlated with mo_sin_rcnt_rev_tl_op and 6 other fieldsHigh correlation
addr_state is highly overall correlated with idHigh correlation
all_util is highly overall correlated with bc_open_to_buy and 4 other fieldsHigh correlation
annual_inc is highly overall correlated with annual_inc_joint and 6 other fieldsHigh correlation
annual_inc_joint is highly overall correlated with annual_inc and 2 other fieldsHigh correlation
application_type is highly overall correlated with annual_inc_joint and 15 other fieldsHigh correlation
avg_cur_bal is highly overall correlated with mort_acc and 2 other fieldsHigh correlation
bc_open_to_buy is highly overall correlated with all_util and 6 other fieldsHigh correlation
bc_util is highly overall correlated with all_util and 3 other fieldsHigh correlation
collection_recovery_fee is highly overall correlated with recoveriesHigh correlation
debt_settlement_flag is highly overall correlated with id and 4 other fieldsHigh correlation
default_flag is highly overall correlated with hardship_status and 4 other fieldsHigh correlation
delinq_2yrs is highly overall correlated with mths_since_last_delinq and 4 other fieldsHigh correlation
delinq_amnt is highly overall correlated with acc_now_delinq and 4 other fieldsHigh correlation
disbursement_method is highly overall correlated with id and 1 other fieldsHigh correlation
dti is highly overall correlated with dti_joint and 1 other fieldsHigh correlation
dti_joint is highly overall correlated with application_type and 2 other fieldsHigh correlation
emp_length is highly overall correlated with idHigh correlation
fico_range_high is highly overall correlated with fico_range_lowHigh correlation
fico_range_low is highly overall correlated with fico_range_highHigh correlation
funded_amnt is highly overall correlated with funded_amnt_inv and 10 other fieldsHigh correlation
funded_amnt_inv is highly overall correlated with funded_amnt and 10 other fieldsHigh correlation
grade is highly overall correlated with id and 2 other fieldsHigh correlation
hardship_amount is highly overall correlated with funded_amnt and 13 other fieldsHigh correlation
hardship_dpd is highly overall correlated with hardship_loan_status and 2 other fieldsHigh correlation
hardship_flag is highly overall correlated with hardship_status and 7 other fieldsHigh correlation
hardship_last_payment_amount is highly overall correlated with dti_joint and 2 other fieldsHigh correlation
hardship_loan_status is highly overall correlated with acc_now_delinq and 9 other fieldsHigh correlation
hardship_payoff_balance_amount is highly overall correlated with annual_inc and 16 other fieldsHigh correlation
hardship_reason is highly overall correlated with acc_now_delinq and 9 other fieldsHigh correlation
hardship_status is highly overall correlated with acc_now_delinq and 15 other fieldsHigh correlation
home_ownership is highly overall correlated with idHigh correlation
id is highly overall correlated with addr_state and 24 other fieldsHigh correlation
il_util is highly overall correlated with all_utilHigh correlation
initial_list_status is highly overall correlated with idHigh correlation
inq_last_12m is highly overall correlated with inq_last_6mths and 2 other fieldsHigh correlation
inq_last_6mths is highly overall correlated with inq_last_12m and 1 other fieldsHigh correlation
installment is highly overall correlated with funded_amnt and 10 other fieldsHigh correlation
int_rate is highly overall correlated with grade and 3 other fieldsHigh correlation
last_fico_range_high is highly overall correlated with default_flag and 1 other fieldsHigh correlation
last_fico_range_low is highly overall correlated with default_flag and 1 other fieldsHigh correlation
last_pymnt_amnt is highly overall correlated with orig_projected_additional_accrued_interest and 5 other fieldsHigh correlation
loan_amnt is highly overall correlated with funded_amnt and 10 other fieldsHigh correlation
loan_status is highly overall correlated with default_flag and 2 other fieldsHigh correlation
max_bal_bc is highly overall correlated with revol_bal and 4 other fieldsHigh correlation
mo_sin_rcnt_rev_tl_op is highly overall correlated with acc_open_past_24mths and 6 other fieldsHigh correlation
mo_sin_rcnt_tl is highly overall correlated with acc_open_past_24mths and 5 other fieldsHigh correlation
mort_acc is highly overall correlated with avg_cur_bal and 3 other fieldsHigh correlation
mths_since_last_delinq is highly overall correlated with delinq_2yrs and 3 other fieldsHigh correlation
mths_since_last_major_derog is highly overall correlated with delinq_2yrs and 4 other fieldsHigh correlation
mths_since_rcnt_il is highly overall correlated with open_il_12m and 1 other fieldsHigh correlation
mths_since_recent_bc is highly overall correlated with mo_sin_rcnt_rev_tl_op and 4 other fieldsHigh correlation
mths_since_recent_bc_dlq is highly overall correlated with delinq_2yrs and 3 other fieldsHigh correlation
mths_since_recent_inq is highly overall correlated with inq_last_12m and 1 other fieldsHigh correlation
mths_since_recent_revol_delinq is highly overall correlated with delinq_2yrs and 3 other fieldsHigh correlation
num_accts_ever_120_pd is highly overall correlated with pct_tl_nvr_dlqHigh correlation
num_actv_bc_tl is highly overall correlated with num_actv_rev_tl and 8 other fieldsHigh correlation
num_actv_rev_tl is highly overall correlated with num_actv_bc_tl and 7 other fieldsHigh correlation
num_bc_sats is highly overall correlated with bc_open_to_buy and 10 other fieldsHigh correlation
num_bc_tl is highly overall correlated with num_actv_bc_tl and 8 other fieldsHigh correlation
num_il_tl is highly overall correlated with open_act_il and 5 other fieldsHigh correlation
num_op_rev_tl is highly overall correlated with num_actv_bc_tl and 10 other fieldsHigh correlation
num_rev_accts is highly overall correlated with num_actv_rev_tl and 8 other fieldsHigh correlation
num_rev_tl_bal_gt_0 is highly overall correlated with num_actv_bc_tl and 7 other fieldsHigh correlation
num_sats is highly overall correlated with num_actv_bc_tl and 9 other fieldsHigh correlation
num_tl_120dpd_2m is highly overall correlated with hardship_amount and 12 other fieldsHigh correlation
num_tl_30dpd is highly overall correlated with acc_now_delinq and 9 other fieldsHigh correlation
num_tl_90g_dpd_24m is highly overall correlated with delinq_2yrs and 1 other fieldsHigh correlation
num_tl_op_past_12m is highly overall correlated with acc_open_past_24mths and 8 other fieldsHigh correlation
open_acc is highly overall correlated with num_actv_bc_tl and 9 other fieldsHigh correlation
open_acc_6m is highly overall correlated with acc_open_past_24mths and 4 other fieldsHigh correlation
open_act_il is highly overall correlated with num_il_tl and 4 other fieldsHigh correlation
open_il_12m is highly overall correlated with mths_since_rcnt_il and 2 other fieldsHigh correlation
open_il_24m is highly overall correlated with acc_open_past_24mths and 5 other fieldsHigh correlation
open_rv_12m is highly overall correlated with acc_open_past_24mths and 6 other fieldsHigh correlation
open_rv_24m is highly overall correlated with acc_open_past_24mths and 5 other fieldsHigh correlation
orig_projected_additional_accrued_interest is highly overall correlated with funded_amnt and 14 other fieldsHigh correlation
out_prncp is highly overall correlated with id and 1 other fieldsHigh correlation
out_prncp_inv is highly overall correlated with id and 1 other fieldsHigh correlation
pct_tl_nvr_dlq is highly overall correlated with num_accts_ever_120_pdHigh correlation
percent_bc_gt_75 is highly overall correlated with all_util and 3 other fieldsHigh correlation
pub_rec is highly overall correlated with pub_rec_bankruptciesHigh correlation
pub_rec_bankruptcies is highly overall correlated with pub_recHigh correlation
purpose is highly overall correlated with idHigh correlation
pymnt_plan is highly overall correlated with hardship_flag and 7 other fieldsHigh correlation
recoveries is highly overall correlated with collection_recovery_feeHigh correlation
revol_bal is highly overall correlated with max_bal_bc and 6 other fieldsHigh correlation
revol_bal_joint is highly overall correlated with application_type and 6 other fieldsHigh correlation
revol_util is highly overall correlated with all_util and 4 other fieldsHigh correlation
sec_app_chargeoff_within_12_mths is highly overall correlated with application_type and 1 other fieldsHigh correlation
sec_app_collections_12_mths_ex_med is highly overall correlated with application_type and 4 other fieldsHigh correlation
sec_app_fico_range_high is highly overall correlated with application_type and 1 other fieldsHigh correlation
sec_app_fico_range_low is highly overall correlated with application_type and 1 other fieldsHigh correlation
sec_app_inq_last_6mths is highly overall correlated with application_typeHigh correlation
sec_app_mort_acc is highly overall correlated with application_type and 3 other fieldsHigh correlation
sec_app_mths_since_last_major_derog is highly overall correlated with application_type and 7 other fieldsHigh correlation
sec_app_num_rev_accts is highly overall correlated with application_type and 3 other fieldsHigh correlation
sec_app_open_acc is highly overall correlated with application_type and 3 other fieldsHigh correlation
sec_app_open_act_il is highly overall correlated with application_type and 2 other fieldsHigh correlation
sec_app_revol_util is highly overall correlated with application_type and 3 other fieldsHigh correlation
settlement_amount is highly overall correlated with debt_settlement_flag and 14 other fieldsHigh correlation
settlement_percentage is highly overall correlated with debt_settlement_flag and 5 other fieldsHigh correlation
settlement_status is highly overall correlated with debt_settlement_flag and 9 other fieldsHigh correlation
settlement_term is highly overall correlated with debt_settlement_flag and 9 other fieldsHigh correlation
sub_grade is highly overall correlated with grade and 2 other fieldsHigh correlation
term is highly overall correlated with idHigh correlation
tot_coll_amt is highly overall correlated with hardship_loan_status and 3 other fieldsHigh correlation
tot_cur_bal is highly overall correlated with annual_inc and 6 other fieldsHigh correlation
tot_hi_cred_lim is highly overall correlated with annual_inc and 9 other fieldsHigh correlation
total_acc is highly overall correlated with num_bc_tl and 5 other fieldsHigh correlation
total_bal_ex_mort is highly overall correlated with num_il_tl and 5 other fieldsHigh correlation
total_bal_il is highly overall correlated with num_il_tl and 5 other fieldsHigh correlation
total_bc_limit is highly overall correlated with bc_open_to_buy and 7 other fieldsHigh correlation
total_il_high_credit_limit is highly overall correlated with num_il_tl and 5 other fieldsHigh correlation
total_pymnt is highly overall correlated with funded_amnt and 10 other fieldsHigh correlation
total_pymnt_inv is highly overall correlated with funded_amnt and 10 other fieldsHigh correlation
total_rec_int is highly overall correlated with funded_amnt and 10 other fieldsHigh correlation
total_rec_prncp is highly overall correlated with funded_amnt and 7 other fieldsHigh correlation
total_rev_hi_lim is highly overall correlated with bc_open_to_buy and 10 other fieldsHigh correlation
verification_status is highly overall correlated with id and 1 other fieldsHigh correlation
verification_status_joint is highly overall correlated with application_type and 6 other fieldsHigh correlation
loan_status is highly imbalanced (51.8%) Imbalance
pymnt_plan is highly imbalanced (99.5%) Imbalance
application_type is highly imbalanced (70.0%) Imbalance
num_tl_120dpd_2m is highly imbalanced (99.6%) Imbalance
num_tl_30dpd is highly imbalanced (98.9%) Imbalance
hardship_flag is highly imbalanced (99.5%) Imbalance
disbursement_method is highly imbalanced (78.5%) Imbalance
debt_settlement_flag is highly imbalanced (88.8%) Imbalance
member_id has 67821 (100.0%) missing values Missing
emp_title has 5112 (7.5%) missing values Missing
emp_length has 4511 (6.7%) missing values Missing
desc has 64023 (94.4%) missing values Missing
title has 694 (1.0%) missing values Missing
mths_since_last_delinq has 34676 (51.1%) missing values Missing
mths_since_last_record has 57008 (84.1%) missing values Missing
next_pymnt_d has 40433 (59.6%) missing values Missing
mths_since_last_major_derog has 50351 (74.2%) missing values Missing
annual_inc_joint has 64214 (94.7%) missing values Missing
dti_joint has 64214 (94.7%) missing values Missing
verification_status_joint has 64357 (94.9%) missing values Missing
tot_coll_amt has 2093 (3.1%) missing values Missing
tot_cur_bal has 2093 (3.1%) missing values Missing
open_acc_6m has 25995 (38.3%) missing values Missing
open_act_il has 25995 (38.3%) missing values Missing
open_il_12m has 25995 (38.3%) missing values Missing
open_il_24m has 25995 (38.3%) missing values Missing
mths_since_rcnt_il has 27257 (40.2%) missing values Missing
total_bal_il has 25995 (38.3%) missing values Missing
il_util has 32034 (47.2%) missing values Missing
open_rv_12m has 25995 (38.3%) missing values Missing
open_rv_24m has 25995 (38.3%) missing values Missing
max_bal_bc has 25995 (38.3%) missing values Missing
all_util has 26003 (38.3%) missing values Missing
total_rev_hi_lim has 2093 (3.1%) missing values Missing
inq_fi has 25995 (38.3%) missing values Missing
total_cu_tl has 25995 (38.3%) missing values Missing
inq_last_12m has 25995 (38.3%) missing values Missing
acc_open_past_24mths has 1485 (2.2%) missing values Missing
avg_cur_bal has 2096 (3.1%) missing values Missing
bc_open_to_buy has 2202 (3.2%) missing values Missing
bc_util has 2235 (3.3%) missing values Missing
mo_sin_old_il_acct has 4131 (6.1%) missing values Missing
mo_sin_old_rev_tl_op has 2093 (3.1%) missing values Missing
mo_sin_rcnt_rev_tl_op has 2093 (3.1%) missing values Missing
mo_sin_rcnt_tl has 2093 (3.1%) missing values Missing
mort_acc has 1485 (2.2%) missing values Missing
mths_since_recent_bc has 2164 (3.2%) missing values Missing
mths_since_recent_bc_dlq has 52121 (76.9%) missing values Missing
mths_since_recent_inq has 8909 (13.1%) missing values Missing
mths_since_recent_revol_delinq has 45580 (67.2%) missing values Missing
num_accts_ever_120_pd has 2093 (3.1%) missing values Missing
num_actv_bc_tl has 2093 (3.1%) missing values Missing
num_actv_rev_tl has 2093 (3.1%) missing values Missing
num_bc_sats has 1740 (2.6%) missing values Missing
num_bc_tl has 2093 (3.1%) missing values Missing
num_il_tl has 2093 (3.1%) missing values Missing
num_op_rev_tl has 2093 (3.1%) missing values Missing
num_rev_accts has 2093 (3.1%) missing values Missing
num_rev_tl_bal_gt_0 has 2093 (3.1%) missing values Missing
num_sats has 1740 (2.6%) missing values Missing
num_tl_120dpd_2m has 4592 (6.8%) missing values Missing
num_tl_30dpd has 2093 (3.1%) missing values Missing
num_tl_90g_dpd_24m has 2093 (3.1%) missing values Missing
num_tl_op_past_12m has 2093 (3.1%) missing values Missing
pct_tl_nvr_dlq has 2097 (3.1%) missing values Missing
percent_bc_gt_75 has 2214 (3.3%) missing values Missing
tot_hi_cred_lim has 2093 (3.1%) missing values Missing
total_bal_ex_mort has 1485 (2.2%) missing values Missing
total_bc_limit has 1485 (2.2%) missing values Missing
total_il_high_credit_limit has 2093 (3.1%) missing values Missing
revol_bal_joint has 64572 (95.2%) missing values Missing
sec_app_fico_range_low has 64572 (95.2%) missing values Missing
sec_app_fico_range_high has 64572 (95.2%) missing values Missing
sec_app_earliest_cr_line has 64572 (95.2%) missing values Missing
sec_app_inq_last_6mths has 64572 (95.2%) missing values Missing
sec_app_mort_acc has 64572 (95.2%) missing values Missing
sec_app_open_acc has 64572 (95.2%) missing values Missing
sec_app_revol_util has 64629 (95.3%) missing values Missing
sec_app_open_act_il has 64572 (95.2%) missing values Missing
sec_app_num_rev_accts has 64572 (95.2%) missing values Missing
sec_app_chargeoff_within_12_mths has 64572 (95.2%) missing values Missing
sec_app_collections_12_mths_ex_med has 64572 (95.2%) missing values Missing
sec_app_mths_since_last_major_derog has 66766 (98.4%) missing values Missing
hardship_type has 67487 (99.5%) missing values Missing
hardship_reason has 67487 (99.5%) missing values Missing
hardship_status has 67487 (99.5%) missing values Missing
deferral_term has 67487 (99.5%) missing values Missing
hardship_amount has 67487 (99.5%) missing values Missing
hardship_start_date has 67487 (99.5%) missing values Missing
hardship_end_date has 67487 (99.5%) missing values Missing
payment_plan_start_date has 67487 (99.5%) missing values Missing
hardship_length has 67487 (99.5%) missing values Missing
hardship_dpd has 67487 (99.5%) missing values Missing
hardship_loan_status has 67487 (99.5%) missing values Missing
orig_projected_additional_accrued_interest has 67543 (99.6%) missing values Missing
hardship_payoff_balance_amount has 67487 (99.5%) missing values Missing
hardship_last_payment_amount has 67487 (99.5%) missing values Missing
debt_settlement_flag_date has 66813 (98.5%) missing values Missing
settlement_status has 66813 (98.5%) missing values Missing
settlement_date has 66813 (98.5%) missing values Missing
settlement_amount has 66813 (98.5%) missing values Missing
settlement_percentage has 66813 (98.5%) missing values Missing
settlement_term has 66813 (98.5%) missing values Missing
dti is highly skewed (γ1 = 31.07494632) Skewed
acc_now_delinq is highly skewed (γ1 = 23.94763261) Skewed
tot_coll_amt is highly skewed (γ1 = 56.80474318) Skewed
delinq_amnt is highly skewed (γ1 = 85.71475138) Skewed
id has unique values Unique
url has unique values Unique
member_id is an unsupported type, check if it needs cleaning or further analysis Unsupported
delinq_2yrs has 55148 (81.3%) zeros Zeros
inq_last_6mths has 41284 (60.9%) zeros Zeros
pub_rec has 57043 (84.1%) zeros Zeros
out_prncp has 40642 (59.9%) zeros Zeros
out_prncp_inv has 40642 (59.9%) zeros Zeros
total_rec_late_fee has 65248 (96.2%) zeros Zeros
recoveries has 62171 (91.7%) zeros Zeros
collection_recovery_fee has 62419 (92.0%) zeros Zeros
last_fico_range_low has 1119 (1.6%) zeros Zeros
collections_12_mths_ex_med has 66688 (98.3%) zeros Zeros
acc_now_delinq has 67579 (99.6%) zeros Zeros
tot_coll_amt has 55687 (82.1%) zeros Zeros
open_acc_6m has 18783 (27.7%) zeros Zeros
open_act_il has 4891 (7.2%) zeros Zeros
open_il_12m has 22734 (33.5%) zeros Zeros
open_il_24m has 11269 (16.6%) zeros Zeros
total_bal_il has 4674 (6.9%) zeros Zeros
open_rv_12m has 15287 (22.5%) zeros Zeros
open_rv_24m has 6776 (10.0%) zeros Zeros
max_bal_bc has 1060 (1.6%) zeros Zeros
inq_fi has 20858 (30.8%) zeros Zeros
total_cu_tl has 22507 (33.2%) zeros Zeros
inq_last_12m has 11943 (17.6%) zeros Zeros
acc_open_past_24mths has 3038 (4.5%) zeros Zeros
bc_open_to_buy has 979 (1.4%) zeros Zeros
bc_util has 849 (1.3%) zeros Zeros
chargeoff_within_12_mths has 67290 (99.2%) zeros Zeros
delinq_amnt has 67629 (99.7%) zeros Zeros
mo_sin_rcnt_rev_tl_op has 966 (1.4%) zeros Zeros
mo_sin_rcnt_tl has 1003 (1.5%) zeros Zeros
mort_acc has 27882 (41.1%) zeros Zeros
mths_since_recent_inq has 5055 (7.5%) zeros Zeros
num_accts_ever_120_pd has 50631 (74.7%) zeros Zeros
num_actv_bc_tl has 1485 (2.2%) zeros Zeros
num_bc_sats has 691 (1.0%) zeros Zeros
num_il_tl has 2041 (3.0%) zeros Zeros
num_tl_90g_dpd_24m has 62217 (91.7%) zeros Zeros
num_tl_op_past_12m has 12386 (18.3%) zeros Zeros
percent_bc_gt_75 has 17924 (26.4%) zeros Zeros
pub_rec_bankruptcies has 59640 (87.9%) zeros Zeros
tax_liens has 65845 (97.1%) zeros Zeros
total_bc_limit has 729 (1.1%) zeros Zeros
total_il_high_credit_limit has 7816 (11.5%) zeros Zeros
sec_app_inq_last_6mths has 1988 (2.9%) zeros Zeros
sec_app_mort_acc has 1332 (2.0%) zeros Zeros
sec_app_chargeoff_within_12_mths has 3159 (4.7%) zeros Zeros
sec_app_collections_12_mths_ex_med has 3057 (4.5%) zeros Zeros

Reproduction

Analysis started2026-01-19 18:06:29.718848
Analysis finished2026-01-19 18:07:28.970130
Duration59.25 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

id
Real number (ℝ)

High correlation  Unique 

Distinct67821
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80243529
Minimum65640
Maximum1.4564315 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:29.024057image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum65640
5-th percentile3371630
Q144815248
median84586990
Q31.2225616 × 108
95-th percentile1.4132789 × 108
Maximum1.4564315 × 108
Range1.4557751 × 108
Interquartile range (IQR)77440911

Descriptive statistics

Standard deviation44936326
Coefficient of variation (CV)0.55999938
Kurtosis-1.1529569
Mean80243529
Median Absolute Deviation (MAD)38421850
Skewness-0.27711262
Sum5.4421964 × 1012
Variance2.0192734 × 1015
MonotonicityNot monotonic
2026-01-19T10:07:29.105133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144657889 1
 
< 0.1%
96404876 1
 
< 0.1%
116270275 1
 
< 0.1%
94716506 1
 
< 0.1%
79044197 1
 
< 0.1%
91443780 1
 
< 0.1%
88766045 1
 
< 0.1%
131832227 1
 
< 0.1%
136649827 1
 
< 0.1%
86985198 1
 
< 0.1%
Other values (67811) 67811
> 99.9%
ValueCountFrequency (%)
65640 1
< 0.1%
85961 1
< 0.1%
92440 1
< 0.1%
92666 1
< 0.1%
99009 1
< 0.1%
115363 1
< 0.1%
119948 1
< 0.1%
127531 1
< 0.1%
130510 1
< 0.1%
131732 1
< 0.1%
ValueCountFrequency (%)
145643149 1
< 0.1%
145618129 1
< 0.1%
145612967 1
< 0.1%
145611625 1
< 0.1%
145609588 1
< 0.1%
145608583 1
< 0.1%
145605420 1
< 0.1%
145604900 1
< 0.1%
145599414 1
< 0.1%
145592181 1
< 0.1%

member_id
Unsupported

Missing  Rejected  Unsupported 

Missing67821
Missing (%)100.0%
Memory size1.0 MiB

loan_amnt
Real number (ℝ)

High correlation 

Distinct1382
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15073.282
Minimum500
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:29.184888image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile3200
Q18000
median13000
Q320000
95-th percentile35000
Maximum40000
Range39500
Interquartile range (IQR)12000

Descriptive statistics

Standard deviation9192.6666
Coefficient of variation (CV)0.60986499
Kurtosis-0.12548201
Mean15073.282
Median Absolute Deviation (MAD)6200
Skewness0.76956537
Sum1.022285 × 109
Variance84505120
MonotonicityNot monotonic
2026-01-19T10:07:29.270155image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 5521
 
8.1%
20000 3922
 
5.8%
15000 3782
 
5.6%
12000 3671
 
5.4%
35000 2578
 
3.8%
5000 2438
 
3.6%
6000 2213
 
3.3%
8000 2117
 
3.1%
16000 2007
 
3.0%
25000 1985
 
2.9%
Other values (1372) 37587
55.4%
ValueCountFrequency (%)
500 1
 
< 0.1%
1000 301
0.4%
1025 1
 
< 0.1%
1050 7
 
< 0.1%
1075 1
 
< 0.1%
1100 9
 
< 0.1%
1125 1
 
< 0.1%
1150 4
 
< 0.1%
1175 2
 
< 0.1%
1200 130
0.2%
ValueCountFrequency (%)
40000 1037
1.5%
39900 1
 
< 0.1%
39875 1
 
< 0.1%
39850 1
 
< 0.1%
39825 2
 
< 0.1%
39775 2
 
< 0.1%
39675 1
 
< 0.1%
39625 1
 
< 0.1%
39600 2
 
< 0.1%
39500 5
 
< 0.1%

funded_amnt
Real number (ℝ)

High correlation 

Distinct1383
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15068.813
Minimum500
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:29.355824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile3200
Q18000
median13000
Q320000
95-th percentile35000
Maximum40000
Range39500
Interquartile range (IQR)12000

Descriptive statistics

Standard deviation9191.4284
Coefficient of variation (CV)0.60996365
Kurtosis-0.12365787
Mean15068.813
Median Absolute Deviation (MAD)6200
Skewness0.77049543
Sum1.021982 × 109
Variance84482357
MonotonicityNot monotonic
2026-01-19T10:07:29.442211image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 5521
 
8.1%
20000 3916
 
5.8%
15000 3781
 
5.6%
12000 3666
 
5.4%
35000 2574
 
3.8%
5000 2437
 
3.6%
6000 2213
 
3.3%
8000 2117
 
3.1%
16000 2006
 
3.0%
25000 1980
 
2.9%
Other values (1373) 37610
55.5%
ValueCountFrequency (%)
500 1
 
< 0.1%
1000 301
0.4%
1025 1
 
< 0.1%
1050 7
 
< 0.1%
1075 1
 
< 0.1%
1100 9
 
< 0.1%
1125 1
 
< 0.1%
1150 4
 
< 0.1%
1175 2
 
< 0.1%
1200 130
0.2%
ValueCountFrequency (%)
40000 1037
1.5%
39900 1
 
< 0.1%
39875 1
 
< 0.1%
39850 1
 
< 0.1%
39825 2
 
< 0.1%
39775 2
 
< 0.1%
39675 1
 
< 0.1%
39625 1
 
< 0.1%
39600 2
 
< 0.1%
39500 5
 
< 0.1%

funded_amnt_inv
Real number (ℝ)

High correlation 

Distinct1664
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15051.964
Minimum0
Maximum40000
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:29.715174image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3200
Q18000
median13000
Q320000
95-th percentile35000
Maximum40000
Range40000
Interquartile range (IQR)12000

Descriptive statistics

Standard deviation9195.4093
Coefficient of variation (CV)0.61091094
Kurtosis-0.12324421
Mean15051.964
Median Absolute Deviation (MAD)6200
Skewness0.770053
Sum1.0208392 × 109
Variance84555552
MonotonicityNot monotonic
2026-01-19T10:07:29.800718image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 5240
 
7.7%
20000 3596
 
5.3%
15000 3532
 
5.2%
12000 3437
 
5.1%
5000 2363
 
3.5%
35000 2268
 
3.3%
6000 2126
 
3.1%
8000 2004
 
3.0%
16000 1870
 
2.8%
25000 1830
 
2.7%
Other values (1654) 39555
58.3%
ValueCountFrequency (%)
0 5
< 0.1%
150 1
 
< 0.1%
195.3439396 1
 
< 0.1%
249.9960013 1
 
< 0.1%
250 1
 
< 0.1%
250.59 1
 
< 0.1%
300 3
< 0.1%
349.9920453 1
 
< 0.1%
349.9999291 1
 
< 0.1%
425.0039285 1
 
< 0.1%
ValueCountFrequency (%)
40000 994
1.5%
39975 16
 
< 0.1%
39950 4
 
< 0.1%
39925 4
 
< 0.1%
39875 1
 
< 0.1%
39850 1
 
< 0.1%
39825 2
 
< 0.1%
39775 2
 
< 0.1%
39750 7
 
< 0.1%
39725 7
 
< 0.1%

term
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
36 months
48289 
60 months
19532 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters678210
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 36 months
2nd row 36 months
3rd row 36 months
4th row 60 months
5th row 36 months

Common Values

ValueCountFrequency (%)
36 months 48289
71.2%
60 months 19532
28.8%

Length

2026-01-19T10:07:29.884429image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:29.944358image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
months 67821
50.0%
36 48289
35.6%
60 19532
 
14.4%

Most occurring characters

ValueCountFrequency (%)
135642
20.0%
6 67821
10.0%
t 67821
10.0%
m 67821
10.0%
o 67821
10.0%
n 67821
10.0%
s 67821
10.0%
h 67821
10.0%
3 48289
 
7.1%
0 19532
 
2.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 678210
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
135642
20.0%
6 67821
10.0%
t 67821
10.0%
m 67821
10.0%
o 67821
10.0%
n 67821
10.0%
s 67821
10.0%
h 67821
10.0%
3 48289
 
7.1%
0 19532
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 678210
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
135642
20.0%
6 67821
10.0%
t 67821
10.0%
m 67821
10.0%
o 67821
10.0%
n 67821
10.0%
s 67821
10.0%
h 67821
10.0%
3 48289
 
7.1%
0 19532
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 678210
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
135642
20.0%
6 67821
10.0%
t 67821
10.0%
m 67821
10.0%
o 67821
10.0%
n 67821
10.0%
s 67821
10.0%
h 67821
10.0%
3 48289
 
7.1%
0 19532
 
2.9%

int_rate
Real number (ℝ)

High correlation 

Distinct548
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.121968
Minimum5.31
Maximum30.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:30.008794image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum5.31
5-th percentile6.49
Q19.58
median12.62
Q315.99
95-th percentile22.15
Maximum30.99
Range25.68
Interquartile range (IQR)6.41

Descriptive statistics

Standard deviation4.8303838
Coefficient of variation (CV)0.36811427
Kurtosis0.55977786
Mean13.121968
Median Absolute Deviation (MAD)3.18
Skewness0.75909953
Sum889945.02
Variance23.332608
MonotonicityNot monotonic
2026-01-19T10:07:30.086783image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.99 1622
 
2.4%
5.32 1397
 
2.1%
10.99 1382
 
2.0%
13.99 1296
 
1.9%
11.49 952
 
1.4%
16.99 934
 
1.4%
12.99 871
 
1.3%
7.89 840
 
1.2%
9.17 821
 
1.2%
14.99 787
 
1.2%
Other values (538) 56919
83.9%
ValueCountFrequency (%)
5.31 262
 
0.4%
5.32 1397
2.1%
5.42 17
 
< 0.1%
5.79 16
 
< 0.1%
5.93 49
 
0.1%
5.99 10
 
< 0.1%
6 17
 
< 0.1%
6.03 375
 
0.6%
6.07 164
 
0.2%
6.08 163
 
0.2%
ValueCountFrequency (%)
30.99 23
< 0.1%
30.94 15
 
< 0.1%
30.89 19
< 0.1%
30.84 23
< 0.1%
30.79 40
0.1%
30.75 32
< 0.1%
30.74 14
 
< 0.1%
30.65 27
< 0.1%
30.49 11
 
< 0.1%
30.17 43
0.1%

installment
Real number (ℝ)

High correlation 

Distinct22729
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean446.7407
Minimum7.61
Maximum1516.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:30.162297image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum7.61
5-th percentile109.36
Q1251.68
median380.98
Q3594.41
95-th percentile985.16
Maximum1516.27
Range1508.66
Interquartile range (IQR)342.73

Descriptive statistics

Standard deviation267.39112
Coefficient of variation (CV)0.59853764
Kurtosis0.66782539
Mean446.7407
Median Absolute Deviation (MAD)158.7
Skewness0.9920892
Sum30298401
Variance71498.013
MonotonicityNot monotonic
2026-01-19T10:07:30.244382image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301.15 141
 
0.2%
332.1 138
 
0.2%
327.34 116
 
0.2%
361.38 114
 
0.2%
602.3 105
 
0.2%
451.73 103
 
0.2%
329.72 77
 
0.1%
498.15 77
 
0.1%
166.05 73
 
0.1%
752.87 73
 
0.1%
Other values (22719) 66804
98.5%
ValueCountFrequency (%)
7.61 1
< 0.1%
16.25 1
< 0.1%
28.82 1
< 0.1%
29.47 1
< 0.1%
30.12 1
< 0.1%
30.33 1
< 0.1%
30.46 2
< 0.1%
30.65 1
< 0.1%
30.71 1
< 0.1%
30.75 1
< 0.1%
ValueCountFrequency (%)
1516.27 1
< 0.1%
1510.58 1
< 0.1%
1507.87 1
< 0.1%
1506.65 1
< 0.1%
1504.85 1
< 0.1%
1500.22 1
< 0.1%
1500.03 1
< 0.1%
1498.3 1
< 0.1%
1486.34 1
< 0.1%
1485.62 1
< 0.1%

grade
Categorical

High correlation 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
B
20094 
C
19427 
A
12737 
D
9867 
E
4117 
Other values (2)
 
1579

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters67821
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowD
2nd rowC
3rd rowC
4th rowA
5th rowB

Common Values

ValueCountFrequency (%)
B 20094
29.6%
C 19427
28.6%
A 12737
18.8%
D 9867
14.5%
E 4117
 
6.1%
F 1215
 
1.8%
G 364
 
0.5%

Length

2026-01-19T10:07:30.327251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:30.397466image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
b 20094
29.6%
c 19427
28.6%
a 12737
18.8%
d 9867
14.5%
e 4117
 
6.1%
f 1215
 
1.8%
g 364
 
0.5%

Most occurring characters

ValueCountFrequency (%)
B 20094
29.6%
C 19427
28.6%
A 12737
18.8%
D 9867
14.5%
E 4117
 
6.1%
F 1215
 
1.8%
G 364
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 20094
29.6%
C 19427
28.6%
A 12737
18.8%
D 9867
14.5%
E 4117
 
6.1%
F 1215
 
1.8%
G 364
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 20094
29.6%
C 19427
28.6%
A 12737
18.8%
D 9867
14.5%
E 4117
 
6.1%
F 1215
 
1.8%
G 364
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 20094
29.6%
C 19427
28.6%
A 12737
18.8%
D 9867
14.5%
E 4117
 
6.1%
F 1215
 
1.8%
G 364
 
0.5%

sub_grade
Categorical

High correlation 

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
C1
 
4308
B4
 
4283
B5
 
4224
B3
 
3971
C2
 
3898
Other values (30)
47137 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters135642
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowD3
2nd rowC2
3rd rowC1
4th rowA5
5th rowB1

Common Values

ValueCountFrequency (%)
C1 4308
 
6.4%
B4 4283
 
6.3%
B5 4224
 
6.2%
B3 3971
 
5.9%
C2 3898
 
5.7%
C3 3876
 
5.7%
C4 3821
 
5.6%
B2 3813
 
5.6%
B1 3803
 
5.6%
C5 3524
 
5.2%
Other values (25) 28300
41.7%

Length

2026-01-19T10:07:30.472842image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
c1 4308
 
6.4%
b4 4283
 
6.3%
b5 4224
 
6.2%
b3 3971
 
5.9%
c2 3898
 
5.7%
c3 3876
 
5.7%
c4 3821
 
5.6%
b2 3813
 
5.6%
b1 3803
 
5.6%
c5 3524
 
5.2%
Other values (25) 28300
41.7%

Most occurring characters

ValueCountFrequency (%)
B 20094
14.8%
C 19427
14.3%
1 14688
10.8%
4 13532
10.0%
5 13222
9.7%
3 13192
9.7%
2 13187
9.7%
A 12737
9.4%
D 9867
7.3%
E 4117
 
3.0%
Other values (2) 1579
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 135642
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 20094
14.8%
C 19427
14.3%
1 14688
10.8%
4 13532
10.0%
5 13222
9.7%
3 13192
9.7%
2 13187
9.7%
A 12737
9.4%
D 9867
7.3%
E 4117
 
3.0%
Other values (2) 1579
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 135642
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 20094
14.8%
C 19427
14.3%
1 14688
10.8%
4 13532
10.0%
5 13222
9.7%
3 13192
9.7%
2 13187
9.7%
A 12737
9.4%
D 9867
7.3%
E 4117
 
3.0%
Other values (2) 1579
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 135642
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 20094
14.8%
C 19427
14.3%
1 14688
10.8%
4 13532
10.0%
5 13222
9.7%
3 13192
9.7%
2 13187
9.7%
A 12737
9.4%
D 9867
7.3%
E 4117
 
3.0%
Other values (2) 1579
 
1.2%

emp_title
Text

Missing 

Distinct29586
Distinct (%)47.2%
Missing5112
Missing (%)7.5%
Memory size1.0 MiB
2026-01-19T10:07:30.612308image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length46
Median length36
Mean length15.589134
Min length1

Characters and Unicode

Total characters977579
Distinct characters99
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24868 ?
Unique (%)39.7%

Sample

1st rowProcurement
2nd rowExecutive Chef
3rd rowTreasurer
4th rowRN
5th rowSpecial Agent
ValueCountFrequency (%)
manager 9240
 
7.2%
director 2461
 
1.9%
assistant 2180
 
1.7%
sales 2133
 
1.7%
supervisor 1797
 
1.4%
specialist 1761
 
1.4%
teacher 1679
 
1.3%
of 1664
 
1.3%
senior 1584
 
1.2%
driver 1562
 
1.2%
Other values (11100) 101709
79.6%
2026-01-19T10:07:30.835577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 104447
 
10.7%
r 84085
 
8.6%
a 76103
 
7.8%
71096
 
7.3%
i 67411
 
6.9%
n 65678
 
6.7%
t 60312
 
6.2%
o 48525
 
5.0%
s 47541
 
4.9%
c 40994
 
4.2%
Other values (89) 311387
31.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 977579
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 104447
 
10.7%
r 84085
 
8.6%
a 76103
 
7.8%
71096
 
7.3%
i 67411
 
6.9%
n 65678
 
6.7%
t 60312
 
6.2%
o 48525
 
5.0%
s 47541
 
4.9%
c 40994
 
4.2%
Other values (89) 311387
31.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 977579
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 104447
 
10.7%
r 84085
 
8.6%
a 76103
 
7.8%
71096
 
7.3%
i 67411
 
6.9%
n 65678
 
6.7%
t 60312
 
6.2%
o 48525
 
5.0%
s 47541
 
4.9%
c 40994
 
4.2%
Other values (89) 311387
31.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 977579
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 104447
 
10.7%
r 84085
 
8.6%
a 76103
 
7.8%
71096
 
7.3%
i 67411
 
6.9%
n 65678
 
6.7%
t 60312
 
6.2%
o 48525
 
5.0%
s 47541
 
4.9%
c 40994
 
4.2%
Other values (89) 311387
31.9%

emp_length
Categorical

High correlation  Missing 

Distinct11
Distinct (%)< 0.1%
Missing4511
Missing (%)6.7%
Memory size1.0 MiB
10+ years
22495 
2 years
6162 
< 1 year
5744 
3 years
5397 
1 year
4416 
Other values (6)
19096 

Length

Max length9
Median length8
Mean length7.7316064
Min length6

Characters and Unicode

Total characters489488
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9 years
2nd row5 years
3rd row1 year
4th row10+ years
5th row10+ years

Common Values

ValueCountFrequency (%)
10+ years 22495
33.2%
2 years 6162
 
9.1%
< 1 year 5744
 
8.5%
3 years 5397
 
8.0%
1 year 4416
 
6.5%
5 years 4151
 
6.1%
4 years 4086
 
6.0%
6 years 3066
 
4.5%
7 years 2766
 
4.1%
8 years 2740
 
4.0%
(Missing) 4511
 
6.7%

Length

2026-01-19T10:07:30.918964image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
years 53150
40.2%
10 22495
17.0%
1 10160
 
7.7%
year 10160
 
7.7%
2 6162
 
4.7%
5744
 
4.3%
3 5397
 
4.1%
5 4151
 
3.1%
4 4086
 
3.1%
6 3066
 
2.3%
Other values (3) 7793
 
5.9%

Most occurring characters

ValueCountFrequency (%)
69054
14.1%
y 63310
12.9%
r 63310
12.9%
a 63310
12.9%
e 63310
12.9%
s 53150
10.9%
1 32655
6.7%
0 22495
 
4.6%
+ 22495
 
4.6%
2 6162
 
1.3%
Other values (8) 30237
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 489488
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
69054
14.1%
y 63310
12.9%
r 63310
12.9%
a 63310
12.9%
e 63310
12.9%
s 53150
10.9%
1 32655
6.7%
0 22495
 
4.6%
+ 22495
 
4.6%
2 6162
 
1.3%
Other values (8) 30237
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 489488
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
69054
14.1%
y 63310
12.9%
r 63310
12.9%
a 63310
12.9%
e 63310
12.9%
s 53150
10.9%
1 32655
6.7%
0 22495
 
4.6%
+ 22495
 
4.6%
2 6162
 
1.3%
Other values (8) 30237
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 489488
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
69054
14.1%
y 63310
12.9%
r 63310
12.9%
a 63310
12.9%
e 63310
12.9%
s 53150
10.9%
1 32655
6.7%
0 22495
 
4.6%
+ 22495
 
4.6%
2 6162
 
1.3%
Other values (8) 30237
6.2%

home_ownership
Categorical

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
MORTGAGE
33341 
RENT
26863 
OWN
7581 
ANY
 
30
OTHER
 
4

Length

Max length8
Median length5
Mean length5.8542487
Min length3

Characters and Unicode

Total characters397041
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMORTGAGE
2nd rowMORTGAGE
3rd rowRENT
4th rowMORTGAGE
5th rowRENT

Common Values

ValueCountFrequency (%)
MORTGAGE 33341
49.2%
RENT 26863
39.6%
OWN 7581
 
11.2%
ANY 30
 
< 0.1%
OTHER 4
 
< 0.1%
NONE 2
 
< 0.1%

Length

2026-01-19T10:07:30.989789image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:31.056260image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
mortgage 33341
49.2%
rent 26863
39.6%
own 7581
 
11.2%
any 30
 
< 0.1%
other 4
 
< 0.1%
none 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
G 66682
16.8%
E 60210
15.2%
R 60208
15.2%
T 60208
15.2%
O 40928
10.3%
N 34478
8.7%
A 33371
8.4%
M 33341
8.4%
W 7581
 
1.9%
Y 30
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 397041
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 66682
16.8%
E 60210
15.2%
R 60208
15.2%
T 60208
15.2%
O 40928
10.3%
N 34478
8.7%
A 33371
8.4%
M 33341
8.4%
W 7581
 
1.9%
Y 30
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 397041
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 66682
16.8%
E 60210
15.2%
R 60208
15.2%
T 60208
15.2%
O 40928
10.3%
N 34478
8.7%
A 33371
8.4%
M 33341
8.4%
W 7581
 
1.9%
Y 30
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 397041
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 66682
16.8%
E 60210
15.2%
R 60208
15.2%
T 60208
15.2%
O 40928
10.3%
N 34478
8.7%
A 33371
8.4%
M 33341
8.4%
W 7581
 
1.9%
Y 30
 
< 0.1%

annual_inc
Real number (ℝ)

High correlation 

Distinct6443
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77758.751
Minimum0
Maximum4182504
Zeros62
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:31.131905image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile27000
Q146000
median65000
Q394000
95-th percentile160000
Maximum4182504
Range4182504
Interquartile range (IQR)48000

Descriptive statistics

Standard deviation60606.422
Coefficient of variation (CV)0.7794161
Kurtosis561.77622
Mean77758.751
Median Absolute Deviation (MAD)22000
Skewness13.405261
Sum5.2736762 × 109
Variance3.6731384 × 109
MonotonicityNot monotonic
2026-01-19T10:07:31.208214image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 2634
 
3.9%
50000 2244
 
3.3%
65000 1911
 
2.8%
80000 1840
 
2.7%
70000 1782
 
2.6%
40000 1767
 
2.6%
75000 1724
 
2.5%
45000 1611
 
2.4%
55000 1568
 
2.3%
100000 1499
 
2.2%
Other values (6433) 49241
72.6%
ValueCountFrequency (%)
0 62
0.1%
1 1
 
< 0.1%
70 1
 
< 0.1%
500 1
 
< 0.1%
1000 4
 
< 0.1%
1200 2
 
< 0.1%
2000 2
 
< 0.1%
2402 1
 
< 0.1%
2800 1
 
< 0.1%
3000 1
 
< 0.1%
ValueCountFrequency (%)
4182504 1
< 0.1%
3000000 1
< 0.1%
2700000 1
< 0.1%
2568000 1
< 0.1%
2162772 1
< 0.1%
2000000 1
< 0.1%
1460000 1
< 0.1%
1370000 1
< 0.1%
1300000 1
< 0.1%
1250000 2
< 0.1%

verification_status
Categorical

High correlation 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
Source Verified
26584 
Not Verified
22268 
Verified
18969 

Length

Max length15
Median length12
Mean length12.05715
Min length8

Characters and Unicode

Total characters817728
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVerified
2nd rowSource Verified
3rd rowVerified
4th rowNot Verified
5th rowNot Verified

Common Values

ValueCountFrequency (%)
Source Verified 26584
39.2%
Not Verified 22268
32.8%
Verified 18969
28.0%

Length

2026-01-19T10:07:31.281189image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:31.342919image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
verified 67821
58.1%
source 26584
 
22.8%
not 22268
 
19.1%

Most occurring characters

ValueCountFrequency (%)
e 162226
19.8%
i 135642
16.6%
r 94405
11.5%
f 67821
8.3%
V 67821
8.3%
d 67821
8.3%
48852
 
6.0%
o 48852
 
6.0%
S 26584
 
3.3%
c 26584
 
3.3%
Other values (3) 71120
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 817728
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 162226
19.8%
i 135642
16.6%
r 94405
11.5%
f 67821
8.3%
V 67821
8.3%
d 67821
8.3%
48852
 
6.0%
o 48852
 
6.0%
S 26584
 
3.3%
c 26584
 
3.3%
Other values (3) 71120
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 817728
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 162226
19.8%
i 135642
16.6%
r 94405
11.5%
f 67821
8.3%
V 67821
8.3%
d 67821
8.3%
48852
 
6.0%
o 48852
 
6.0%
S 26584
 
3.3%
c 26584
 
3.3%
Other values (3) 71120
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 817728
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 162226
19.8%
i 135642
16.6%
r 94405
11.5%
f 67821
8.3%
V 67821
8.3%
d 67821
8.3%
48852
 
6.0%
o 48852
 
6.0%
S 26584
 
3.3%
c 26584
 
3.3%
Other values (3) 71120
8.7%
Distinct139
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
Minimum2007-06-01 00:00:00
Maximum2018-12-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:31.411448image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:31.496450image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

loan_status
Categorical

High correlation  Imbalance 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
Fully Paid
32326 
Current
26319 
Charged Off
8107 
Late (31-120 days)
 
610
In Grace Period
 
233
Other values (4)
 
226

Length

Max length51
Median length50
Mean length9.0999248
Min length7

Characters and Unicode

Total characters617166
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCharged Off
2nd rowCurrent
3rd rowCurrent
4th rowFully Paid
5th rowFully Paid

Common Values

ValueCountFrequency (%)
Fully Paid 32326
47.7%
Current 26319
38.8%
Charged Off 8107
 
12.0%
Late (31-120 days) 610
 
0.9%
In Grace Period 233
 
0.3%
Late (16-30 days) 158
 
0.2%
Does not meet the credit policy. Status:Fully Paid 45
 
0.1%
Does not meet the credit policy. Status:Charged Off 21
 
< 0.1%
Default 2
 
< 0.1%

Length

2026-01-19T10:07:31.581962image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:31.652087image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
paid 32371
29.2%
fully 32326
29.2%
current 26319
23.8%
off 8128
 
7.3%
charged 8107
 
7.3%
late 768
 
0.7%
days 768
 
0.7%
31-120 610
 
0.6%
in 233
 
0.2%
grace 233
 
0.2%
Other values (11) 855
 
0.8%

Most occurring characters

ValueCountFrequency (%)
l 64810
 
10.5%
r 61298
 
9.9%
u 58758
 
9.5%
42897
 
7.0%
a 42336
 
6.9%
d 41566
 
6.7%
e 36013
 
5.8%
C 34447
 
5.6%
y 33205
 
5.4%
i 32736
 
5.3%
Other values (28) 169100
27.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 617166
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 64810
 
10.5%
r 61298
 
9.9%
u 58758
 
9.5%
42897
 
7.0%
a 42336
 
6.9%
d 41566
 
6.7%
e 36013
 
5.8%
C 34447
 
5.6%
y 33205
 
5.4%
i 32736
 
5.3%
Other values (28) 169100
27.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 617166
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 64810
 
10.5%
r 61298
 
9.9%
u 58758
 
9.5%
42897
 
7.0%
a 42336
 
6.9%
d 41566
 
6.7%
e 36013
 
5.8%
C 34447
 
5.6%
y 33205
 
5.4%
i 32736
 
5.3%
Other values (28) 169100
27.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 617166
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 64810
 
10.5%
r 61298
 
9.9%
u 58758
 
9.5%
42897
 
7.0%
a 42336
 
6.9%
d 41566
 
6.7%
e 36013
 
5.8%
C 34447
 
5.6%
y 33205
 
5.4%
i 32736
 
5.3%
Other values (28) 169100
27.4%

pymnt_plan
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size596.1 KiB
False
67797 
True
 
24
ValueCountFrequency (%)
False 67797
> 99.9%
True 24
 
< 0.1%
2026-01-19T10:07:31.730526image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

url
Text

Unique 

Distinct67821
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:31.848289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length66
Median length65
Mean length65.266333
Min length62

Characters and Unicode

Total characters4426428
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67821 ?
Unique (%)100.0%

Sample

1st rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=96404876
2nd rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=116270275
3rd rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=94716506
4th rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=79044197
5th rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=91443780
ValueCountFrequency (%)
https://lendingclub.com/browse/loandetail.action?loan_id=29795278 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=144657889 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=96404876 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=116270275 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=94716506 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=79044197 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=91443780 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=88766045 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=131832227 1
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=136649827 1
 
< 0.1%
Other values (67811) 67811
> 99.9%
2026-01-19T10:07:32.067830image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 339105
 
7.7%
n 339105
 
7.7%
l 339105
 
7.7%
/ 271284
 
6.1%
a 271284
 
6.1%
t 271284
 
6.1%
i 271284
 
6.1%
c 203463
 
4.6%
e 203463
 
4.6%
. 135642
 
3.1%
Other values (25) 1781409
40.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4426428
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 339105
 
7.7%
n 339105
 
7.7%
l 339105
 
7.7%
/ 271284
 
6.1%
a 271284
 
6.1%
t 271284
 
6.1%
i 271284
 
6.1%
c 203463
 
4.6%
e 203463
 
4.6%
. 135642
 
3.1%
Other values (25) 1781409
40.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4426428
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 339105
 
7.7%
n 339105
 
7.7%
l 339105
 
7.7%
/ 271284
 
6.1%
a 271284
 
6.1%
t 271284
 
6.1%
i 271284
 
6.1%
c 203463
 
4.6%
e 203463
 
4.6%
. 135642
 
3.1%
Other values (25) 1781409
40.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4426428
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 339105
 
7.7%
n 339105
 
7.7%
l 339105
 
7.7%
/ 271284
 
6.1%
a 271284
 
6.1%
t 271284
 
6.1%
i 271284
 
6.1%
c 203463
 
4.6%
e 203463
 
4.6%
. 135642
 
3.1%
Other values (25) 1781409
40.2%

desc
Text

Missing 

Distinct3788
Distinct (%)99.7%
Missing64023
Missing (%)94.4%
Memory size1.0 MiB
2026-01-19T10:07:32.229507image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3616
Median length765
Mean length229.63323
Min length1

Characters and Unicode

Total characters872147
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3786 ?
Unique (%)99.7%

Sample

1st rowloan will be used for paying off credit card.
2nd row Borrower added on 03/03/14 > I am consolidating high-interest credit card debt into one monthly payment with a better interest rate for a 3 year term.<br><br> Borrower added on 03/04/14 > Right now, I pay a around $450/month to separate credit cards and the balance never goes down. With this loan, the payment is about $100/month but at least there is an end in sight after 3 years. I just want to have one neat monthly payment with a finish line at the end.<br><br> Borrower added on 03/05/14 > Sorry, I meant the payment on this loan is $100/month more than what I pay right now.<br><br> Borrower added on 03/06/14 > Thank you to all the investors that have helped fund this loan. I really appreciate it.<br>
3rd row Borrower added on 06/19/12 > I am trying to get rid of all of my credit cards, I have already cut them up and asked them for a lower rate but these companies do not want to help the consumer. I would like to be able to know that I am only 36 months away from being done with them for good. Thank you in advance for your support.<br><br> Borrower added on 06/19/12 > We are tired of the cycle of paying down debt on credit cards only to end up charging them back up again. I want to close our credit accounts and be able to count the days until we are completely done with the rat race circle.<br>
4th row Borrower added on 04/12/10 > I am a responsible professional with a contract for employment that will span the years of this loan. I am single and have relatively low living expenses. I also have a strong credit score.<br/>I recently purchased a Honda Accord- which is the credit inquiry on my credit. I financed $20,000 for the $31,000 car since my past car was paid off and I traded my car in.<br/>
5th row Borrower added on 08/21/12 > The loan is for home improvement on the exterior and back yard of my home<br><br> Borrower added on 08/27/12 > Home improvement to the exterior and back yard of my home because I desire to stay in this home at least for the next 20 years.<br><br> Borrower added on 08/29/12 > I assure that this home improvement will demonstrate to other neighbors the importance of my committment to keep our neighborhood looking great!<br>
ValueCountFrequency (%)
to 6052
 
3.9%
on 5553
 
3.6%
i 5129
 
3.3%
4629
 
3.0%
borrower 4367
 
2.8%
added 4365
 
2.8%
and 4011
 
2.6%
my 3720
 
2.4%
a 3683
 
2.4%
the 3190
 
2.0%
Other values (9880) 111269
71.3%
2026-01-19T10:07:32.486834image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162476
18.6%
e 70439
 
8.1%
o 58352
 
6.7%
a 53073
 
6.1%
r 49782
 
5.7%
t 47028
 
5.4%
n 44884
 
5.1%
d 37579
 
4.3%
i 35600
 
4.1%
s 29270
 
3.4%
Other values (88) 283664
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 872147
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
162476
18.6%
e 70439
 
8.1%
o 58352
 
6.7%
a 53073
 
6.1%
r 49782
 
5.7%
t 47028
 
5.4%
n 44884
 
5.1%
d 37579
 
4.3%
i 35600
 
4.1%
s 29270
 
3.4%
Other values (88) 283664
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 872147
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
162476
18.6%
e 70439
 
8.1%
o 58352
 
6.7%
a 53073
 
6.1%
r 49782
 
5.7%
t 47028
 
5.4%
n 44884
 
5.1%
d 37579
 
4.3%
i 35600
 
4.1%
s 29270
 
3.4%
Other values (88) 283664
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 872147
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
162476
18.6%
e 70439
 
8.1%
o 58352
 
6.7%
a 53073
 
6.1%
r 49782
 
5.7%
t 47028
 
5.4%
n 44884
 
5.1%
d 37579
 
4.3%
i 35600
 
4.1%
s 29270
 
3.4%
Other values (88) 283664
32.5%

purpose
Categorical

High correlation 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
debt_consolidation
38524 
credit_card
15414 
home_improvement
4559 
other
4157 
major_purchase
 
1455
Other values (9)
 
3712

Length

Max length18
Median length18
Mean length14.817239
Min length3

Characters and Unicode

Total characters1004920
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdebt_consolidation
2nd rowdebt_consolidation
3rd rowdebt_consolidation
4th rowcredit_card
5th rowcredit_card

Common Values

ValueCountFrequency (%)
debt_consolidation 38524
56.8%
credit_card 15414
22.7%
home_improvement 4559
 
6.7%
other 4157
 
6.1%
major_purchase 1455
 
2.1%
medical 823
 
1.2%
car 717
 
1.1%
small_business 717
 
1.1%
vacation 445
 
0.7%
house 440
 
0.6%
Other values (4) 570
 
0.8%

Length

2026-01-19T10:07:32.565509image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
debt_consolidation 38524
56.8%
credit_card 15414
22.7%
home_improvement 4559
 
6.7%
other 4157
 
6.1%
major_purchase 1455
 
2.1%
medical 823
 
1.2%
car 717
 
1.1%
small_business 717
 
1.1%
vacation 445
 
0.7%
house 440
 
0.6%
Other values (4) 570
 
0.8%

Most occurring characters

ValueCountFrequency (%)
o 131619
13.1%
d 108887
10.8%
t 101641
10.1%
i 99523
9.9%
n 83392
8.3%
e 75575
7.5%
c 72810
7.2%
_ 60722
 
6.0%
a 60084
 
6.0%
s 43287
 
4.3%
Other values (12) 167380
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1004920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 131619
13.1%
d 108887
10.8%
t 101641
10.1%
i 99523
9.9%
n 83392
8.3%
e 75575
7.5%
c 72810
7.2%
_ 60722
 
6.0%
a 60084
 
6.0%
s 43287
 
4.3%
Other values (12) 167380
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1004920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 131619
13.1%
d 108887
10.8%
t 101641
10.1%
i 99523
9.9%
n 83392
8.3%
e 75575
7.5%
c 72810
7.2%
_ 60722
 
6.0%
a 60084
 
6.0%
s 43287
 
4.3%
Other values (12) 167380
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1004920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 131619
13.1%
d 108887
10.8%
t 101641
10.1%
i 99523
9.9%
n 83392
8.3%
e 75575
7.5%
c 72810
7.2%
_ 60722
 
6.0%
a 60084
 
6.0%
s 43287
 
4.3%
Other values (12) 167380
16.7%

title
Text

Missing 

Distinct3031
Distinct (%)4.5%
Missing694
Missing (%)1.0%
Memory size1.0 MiB
2026-01-19T10:07:32.736512image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length80
Median length18
Mean length17.6843
Min length2

Characters and Unicode

Total characters1187094
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2619 ?
Unique (%)3.9%

Sample

1st rowDebt consolidation
2nd rowDebt consolidation
3rd rowDebt consolidation
4th rowCredit card refinancing
5th rowCredit card refinancing
ValueCountFrequency (%)
debt 36353
24.9%
consolidation 36323
24.9%
credit 14933
10.2%
card 14673
10.0%
refinancing 14036
 
9.6%
home 4836
 
3.3%
improvement 4321
 
3.0%
other 3815
 
2.6%
purchase 1305
 
0.9%
major 1288
 
0.9%
Other values (1781) 14202
 
9.7%
2026-01-19T10:07:33.013893image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 128499
10.8%
i 126582
10.7%
o 125432
10.6%
t 98638
 
8.3%
e 92452
 
7.8%
79180
 
6.7%
a 75631
 
6.4%
d 69142
 
5.8%
c 68454
 
5.8%
r 57592
 
4.9%
Other values (74) 265492
22.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1187094
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 128499
10.8%
i 126582
10.7%
o 125432
10.6%
t 98638
 
8.3%
e 92452
 
7.8%
79180
 
6.7%
a 75631
 
6.4%
d 69142
 
5.8%
c 68454
 
5.8%
r 57592
 
4.9%
Other values (74) 265492
22.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1187094
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 128499
10.8%
i 126582
10.7%
o 125432
10.6%
t 98638
 
8.3%
e 92452
 
7.8%
79180
 
6.7%
a 75631
 
6.4%
d 69142
 
5.8%
c 68454
 
5.8%
r 57592
 
4.9%
Other values (74) 265492
22.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1187094
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 128499
10.8%
i 126582
10.7%
o 125432
10.6%
t 98638
 
8.3%
e 92452
 
7.8%
79180
 
6.7%
a 75631
 
6.4%
d 69142
 
5.8%
c 68454
 
5.8%
r 57592
 
4.9%
Other values (74) 265492
22.4%
Distinct874
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:33.186150image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters339105
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)< 0.1%

Sample

1st row773xx
2nd row548xx
3rd row322xx
4th row609xx
5th row941xx
ValueCountFrequency (%)
750xx 765
 
1.1%
112xx 711
 
1.0%
945xx 668
 
1.0%
300xx 630
 
0.9%
606xx 628
 
0.9%
331xx 576
 
0.8%
770xx 559
 
0.8%
070xx 530
 
0.8%
900xx 530
 
0.8%
100xx 529
 
0.8%
Other values (864) 61695
91.0%
2026-01-19T10:07:33.436752image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
x 135642
40.0%
0 30257
 
8.9%
1 24376
 
7.2%
3 22703
 
6.7%
2 21433
 
6.3%
7 20255
 
6.0%
9 19684
 
5.8%
4 17551
 
5.2%
8 16310
 
4.8%
5 16030
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 339105
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
x 135642
40.0%
0 30257
 
8.9%
1 24376
 
7.2%
3 22703
 
6.7%
2 21433
 
6.3%
7 20255
 
6.0%
9 19684
 
5.8%
4 17551
 
5.2%
8 16310
 
4.8%
5 16030
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 339105
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
x 135642
40.0%
0 30257
 
8.9%
1 24376
 
7.2%
3 22703
 
6.7%
2 21433
 
6.3%
7 20255
 
6.0%
9 19684
 
5.8%
4 17551
 
5.2%
8 16310
 
4.8%
5 16030
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 339105
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
x 135642
40.0%
0 30257
 
8.9%
1 24376
 
7.2%
3 22703
 
6.7%
2 21433
 
6.3%
7 20255
 
6.0%
9 19684
 
5.8%
4 17551
 
5.2%
8 16310
 
4.8%
5 16030
 
4.7%

addr_state
Categorical

High correlation 

Distinct50
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
CA
9400 
NY
5700 
TX
5528 
FL
4833 
IL
 
2765
Other values (45)
39595 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters135642
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTX
2nd rowWI
3rd rowFL
4th rowIL
5th rowCA

Common Values

ValueCountFrequency (%)
CA 9400
 
13.9%
NY 5700
 
8.4%
TX 5528
 
8.2%
FL 4833
 
7.1%
IL 2765
 
4.1%
NJ 2437
 
3.6%
PA 2307
 
3.4%
GA 2241
 
3.3%
OH 2215
 
3.3%
VA 1984
 
2.9%
Other values (40) 28411
41.9%

Length

2026-01-19T10:07:33.518006image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ca 9400
 
13.9%
ny 5700
 
8.4%
tx 5528
 
8.2%
fl 4833
 
7.1%
il 2765
 
4.1%
nj 2437
 
3.6%
pa 2307
 
3.4%
ga 2241
 
3.3%
oh 2215
 
3.3%
va 1984
 
2.9%
Other values (40) 28411
41.9%

Most occurring characters

ValueCountFrequency (%)
A 22783
16.8%
N 15368
11.3%
C 14793
10.9%
L 9220
 
6.8%
T 8522
 
6.3%
M 8298
 
6.1%
I 7343
 
5.4%
Y 6477
 
4.8%
O 6094
 
4.5%
X 5528
 
4.1%
Other values (14) 31216
23.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 135642
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 22783
16.8%
N 15368
11.3%
C 14793
10.9%
L 9220
 
6.8%
T 8522
 
6.3%
M 8298
 
6.1%
I 7343
 
5.4%
Y 6477
 
4.8%
O 6094
 
4.5%
X 5528
 
4.1%
Other values (14) 31216
23.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 135642
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 22783
16.8%
N 15368
11.3%
C 14793
10.9%
L 9220
 
6.8%
T 8522
 
6.3%
M 8298
 
6.1%
I 7343
 
5.4%
Y 6477
 
4.8%
O 6094
 
4.5%
X 5528
 
4.1%
Other values (14) 31216
23.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 135642
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 22783
16.8%
N 15368
11.3%
C 14793
10.9%
L 9220
 
6.8%
T 8522
 
6.3%
M 8298
 
6.1%
I 7343
 
5.4%
Y 6477
 
4.8%
O 6094
 
4.5%
X 5528
 
4.1%
Other values (14) 31216
23.0%

dti
Real number (ℝ)

High correlation  Skewed 

Distinct4720
Distinct (%)7.0%
Missing63
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean18.937623
Minimum0
Maximum999
Zeros51
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:33.705264image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.97
Q111.96
median17.89
Q324.64
95-th percentile33.92
Maximum999
Range999
Interquartile range (IQR)12.68

Descriptive statistics

Standard deviation15.220299
Coefficient of variation (CV)0.80370695
Kurtosis1787.7685
Mean18.937623
Median Absolute Deviation (MAD)6.3
Skewness31.074946
Sum1283175.5
Variance231.65751
MonotonicityNot monotonic
2026-01-19T10:07:33.788040image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.8 60
 
0.1%
19.2 56
 
0.1%
18 55
 
0.1%
0 51
 
0.1%
16.43 48
 
0.1%
11.76 48
 
0.1%
15.2 47
 
0.1%
14.81 46
 
0.1%
14.85 46
 
0.1%
16.36 46
 
0.1%
Other values (4710) 67255
99.2%
(Missing) 63
 
0.1%
ValueCountFrequency (%)
0 51
0.1%
0.01 1
 
< 0.1%
0.05 1
 
< 0.1%
0.06 1
 
< 0.1%
0.07 1
 
< 0.1%
0.1 1
 
< 0.1%
0.11 2
 
< 0.1%
0.12 1
 
< 0.1%
0.13 1
 
< 0.1%
0.14 2
 
< 0.1%
ValueCountFrequency (%)
999 6
< 0.1%
797.1 1
 
< 0.1%
690.18 1
 
< 0.1%
669.88 1
 
< 0.1%
545.05 1
 
< 0.1%
442.5 1
 
< 0.1%
358.76 1
 
< 0.1%
352.51 1
 
< 0.1%
343.37 1
 
< 0.1%
334.1 1
 
< 0.1%

delinq_2yrs
Real number (ℝ)

High correlation  Zeros 

Distinct21
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.30524919
Minimum0
Maximum24
Zeros55148
Zeros (%)81.3%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:33.854640image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.85525302
Coefficient of variation (CV)2.8018191
Kurtosis60.636716
Mean0.30524919
Median Absolute Deviation (MAD)0
Skewness5.7177958
Sum20702
Variance0.73145772
MonotonicityNot monotonic
2026-01-19T10:07:33.920833image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 55148
81.3%
1 8459
 
12.5%
2 2478
 
3.7%
3 896
 
1.3%
4 364
 
0.5%
5 208
 
0.3%
6 103
 
0.2%
7 58
 
0.1%
8 43
 
0.1%
9 16
 
< 0.1%
Other values (11) 47
 
0.1%
ValueCountFrequency (%)
0 55148
81.3%
1 8459
 
12.5%
2 2478
 
3.7%
3 896
 
1.3%
4 364
 
0.5%
5 208
 
0.3%
6 103
 
0.2%
7 58
 
0.1%
8 43
 
0.1%
9 16
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
20 2
 
< 0.1%
18 1
 
< 0.1%
17 1
 
< 0.1%
16 2
 
< 0.1%
15 1
 
< 0.1%
14 2
 
< 0.1%
13 8
< 0.1%
12 8
< 0.1%
11 7
< 0.1%
Distinct637
Distinct (%)0.9%
Missing1
Missing (%)< 0.1%
Memory size1.0 MiB
Minimum1954-01-01 00:00:00
Maximum2015-11-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:33.993896image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:34.084520image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

fico_range_low
Real number (ℝ)

High correlation 

Distinct43
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean698.59557
Minimum625
Maximum845
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:34.171439image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum625
5-th percentile660
Q1675
median690
Q3715
95-th percentile765
Maximum845
Range220
Interquartile range (IQR)40

Descriptive statistics

Standard deviation32.999597
Coefficient of variation (CV)0.047237055
Kurtosis1.3493002
Mean698.59557
Median Absolute Deviation (MAD)20
Skewness1.1952891
Sum47379450
Variance1088.9734
MonotonicityNot monotonic
2026-01-19T10:07:34.247525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
660 5684
 
8.4%
670 5427
 
8.0%
665 5325
 
7.9%
680 5090
 
7.5%
675 4903
 
7.2%
685 4448
 
6.6%
690 4285
 
6.3%
695 3862
 
5.7%
700 3823
 
5.6%
705 3453
 
5.1%
Other values (33) 21521
31.7%
ValueCountFrequency (%)
625 1
 
< 0.1%
640 3
 
< 0.1%
645 1
 
< 0.1%
650 6
 
< 0.1%
655 5
 
< 0.1%
660 5684
8.4%
665 5325
7.9%
670 5427
8.0%
675 4903
7.2%
680 5090
7.5%
ValueCountFrequency (%)
845 16
 
< 0.1%
840 23
 
< 0.1%
835 25
 
< 0.1%
830 48
 
0.1%
825 53
 
0.1%
820 86
 
0.1%
815 132
0.2%
810 146
0.2%
805 197
0.3%
800 251
0.4%

fico_range_high
Real number (ℝ)

High correlation 

Distinct43
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean702.5958
Minimum629
Maximum850
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:34.321429image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum629
5-th percentile664
Q1679
median694
Q3719
95-th percentile769
Maximum850
Range221
Interquartile range (IQR)40

Descriptive statistics

Standard deviation33.000648
Coefficient of variation (CV)0.046969605
Kurtosis1.3512352
Mean702.5958
Median Absolute Deviation (MAD)20
Skewness1.1955786
Sum47650750
Variance1089.0427
MonotonicityNot monotonic
2026-01-19T10:07:34.396039image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
664 5684
 
8.4%
674 5427
 
8.0%
669 5325
 
7.9%
684 5090
 
7.5%
679 4903
 
7.2%
689 4448
 
6.6%
694 4285
 
6.3%
699 3862
 
5.7%
704 3823
 
5.6%
709 3453
 
5.1%
Other values (33) 21521
31.7%
ValueCountFrequency (%)
629 1
 
< 0.1%
644 3
 
< 0.1%
649 1
 
< 0.1%
654 6
 
< 0.1%
659 5
 
< 0.1%
664 5684
8.4%
669 5325
7.9%
674 5427
8.0%
679 4903
7.2%
684 5090
7.5%
ValueCountFrequency (%)
850 16
 
< 0.1%
844 23
 
< 0.1%
839 25
 
< 0.1%
834 48
 
0.1%
829 53
 
0.1%
824 86
 
0.1%
819 132
0.2%
814 146
0.2%
809 197
0.3%
804 251
0.4%

inq_last_6mths
Real number (ℝ)

High correlation  Zeros 

Distinct11
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.58083161
Minimum0
Maximum18
Zeros41284
Zeros (%)60.9%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:34.456931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.88498621
Coefficient of variation (CV)1.5236537
Kurtosis6.4685466
Mean0.58083161
Median Absolute Deviation (MAD)0
Skewness1.9511436
Sum39392
Variance0.78320059
MonotonicityNot monotonic
2026-01-19T10:07:34.518609image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 41284
60.9%
1 17586
25.9%
2 6091
 
9.0%
3 2125
 
3.1%
4 500
 
0.7%
5 181
 
0.3%
6 44
 
0.1%
7 4
 
< 0.1%
8 3
 
< 0.1%
18 1
 
< 0.1%
ValueCountFrequency (%)
0 41284
60.9%
1 17586
25.9%
2 6091
 
9.0%
3 2125
 
3.1%
4 500
 
0.7%
5 181
 
0.3%
6 44
 
0.1%
7 4
 
< 0.1%
8 3
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
10 1
 
< 0.1%
8 3
 
< 0.1%
7 4
 
< 0.1%
6 44
 
0.1%
5 181
 
0.3%
4 500
 
0.7%
3 2125
 
3.1%
2 6091
 
9.0%
1 17586
25.9%

mths_since_last_delinq
Real number (ℝ)

High correlation  Missing 

Distinct115
Distinct (%)0.3%
Missing34676
Missing (%)51.1%
Infinite0
Infinite (%)0.0%
Mean34.594268
Minimum0
Maximum146
Zeros63
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:34.591705image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q116
median32
Q350
95-th percentile75
Maximum146
Range146
Interquartile range (IQR)34

Descriptive statistics

Standard deviation21.911203
Coefficient of variation (CV)0.6333767
Kurtosis-0.78206301
Mean34.594268
Median Absolute Deviation (MAD)17
Skewness0.44091372
Sum1146627
Variance480.10082
MonotonicityNot monotonic
2026-01-19T10:07:34.674010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 642
 
0.9%
13 626
 
0.9%
6 610
 
0.9%
14 606
 
0.9%
7 605
 
0.9%
8 604
 
0.9%
15 602
 
0.9%
10 602
 
0.9%
11 599
 
0.9%
9 598
 
0.9%
Other values (105) 27051
39.9%
(Missing) 34676
51.1%
ValueCountFrequency (%)
0 63
 
0.1%
1 201
 
0.3%
2 289
0.4%
3 409
0.6%
4 485
0.7%
5 533
0.8%
6 610
0.9%
7 605
0.9%
8 604
0.9%
9 598
0.9%
ValueCountFrequency (%)
146 1
< 0.1%
126 1
< 0.1%
120 2
< 0.1%
118 2
< 0.1%
116 1
< 0.1%
115 1
< 0.1%
113 2
< 0.1%
112 1
< 0.1%
110 1
< 0.1%
106 1
< 0.1%

mths_since_last_record
Real number (ℝ)

Missing 

Distinct122
Distinct (%)1.1%
Missing57008
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean72.037085
Minimum0
Maximum126
Zeros36
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:34.756612image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.6
Q155
median74
Q392
95-th percentile113
Maximum126
Range126
Interquartile range (IQR)37

Descriptive statistics

Standard deviation26.515525
Coefficient of variation (CV)0.3680816
Kurtosis-0.42858803
Mean72.037085
Median Absolute Deviation (MAD)18
Skewness-0.35266469
Sum778937
Variance703.07308
MonotonicityNot monotonic
2026-01-19T10:07:34.842685image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 194
 
0.3%
67 178
 
0.3%
75 172
 
0.3%
72 166
 
0.2%
62 164
 
0.2%
84 162
 
0.2%
81 162
 
0.2%
78 160
 
0.2%
66 159
 
0.2%
76 157
 
0.2%
Other values (112) 9139
 
13.5%
(Missing) 57008
84.1%
ValueCountFrequency (%)
0 36
0.1%
1 2
 
< 0.1%
2 7
 
< 0.1%
3 5
 
< 0.1%
4 10
 
< 0.1%
5 19
< 0.1%
6 19
< 0.1%
7 13
 
< 0.1%
8 19
< 0.1%
9 11
 
< 0.1%
ValueCountFrequency (%)
126 1
 
< 0.1%
121 2
 
< 0.1%
119 37
 
0.1%
118 79
0.1%
117 91
0.1%
116 83
0.1%
115 93
0.1%
114 85
0.1%
113 95
0.1%
112 96
0.1%

open_acc
Real number (ℝ)

High correlation 

Distinct60
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean11.607977
Minimum0
Maximum94
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:34.920932image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q18
median11
Q314
95-th percentile22
Maximum94
Range94
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.6468364
Coefficient of variation (CV)0.48646172
Kurtosis3.7268159
Mean11.607977
Median Absolute Deviation (MAD)3
Skewness1.3305332
Sum787253
Variance31.886762
MonotonicityNot monotonic
2026-01-19T10:07:34.998201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 5854
 
8.6%
8 5735
 
8.5%
10 5603
 
8.3%
11 5271
 
7.8%
7 5247
 
7.7%
12 4622
 
6.8%
6 4425
 
6.5%
13 4108
 
6.1%
14 3570
 
5.3%
5 3185
 
4.7%
Other values (50) 20200
29.8%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 61
 
0.1%
2 322
 
0.5%
3 935
 
1.4%
4 2086
 
3.1%
5 3185
4.7%
6 4425
6.5%
7 5247
7.7%
8 5735
8.5%
9 5854
8.6%
ValueCountFrequency (%)
94 1
 
< 0.1%
66 1
 
< 0.1%
61 1
 
< 0.1%
60 1
 
< 0.1%
57 1
 
< 0.1%
56 2
< 0.1%
53 2
< 0.1%
52 2
< 0.1%
51 4
< 0.1%
50 1
 
< 0.1%

pub_rec
Real number (ℝ)

High correlation  Zeros 

Distinct16
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.19764081
Minimum0
Maximum24
Zeros57043
Zeros (%)84.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:35.065976image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.55892975
Coefficient of variation (CV)2.8280077
Kurtosis131.84474
Mean0.19764081
Median Absolute Deviation (MAD)0
Skewness6.8980795
Sum13404
Variance0.31240246
MonotonicityNot monotonic
2026-01-19T10:07:35.132272image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 57043
84.1%
1 9206
 
13.6%
2 1034
 
1.5%
3 310
 
0.5%
4 119
 
0.2%
5 48
 
0.1%
6 26
 
< 0.1%
7 9
 
< 0.1%
8 8
 
< 0.1%
9 7
 
< 0.1%
Other values (6) 10
 
< 0.1%
ValueCountFrequency (%)
0 57043
84.1%
1 9206
 
13.6%
2 1034
 
1.5%
3 310
 
0.5%
4 119
 
0.2%
5 48
 
0.1%
6 26
 
< 0.1%
7 9
 
< 0.1%
8 8
 
< 0.1%
9 7
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
20 1
 
< 0.1%
19 1
 
< 0.1%
12 1
 
< 0.1%
11 3
 
< 0.1%
10 3
 
< 0.1%
9 7
 
< 0.1%
8 8
 
< 0.1%
7 9
 
< 0.1%
6 26
< 0.1%

revol_bal
Real number (ℝ)

High correlation 

Distinct31351
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16625.099
Minimum0
Maximum1101954
Zeros341
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:35.205798image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1595
Q15931
median11345
Q320322
95-th percentile45463
Maximum1101954
Range1101954
Interquartile range (IQR)14391

Descriptive statistics

Standard deviation21952.052
Coefficient of variation (CV)1.3204163
Kurtosis251.5847
Mean16625.099
Median Absolute Deviation (MAD)6414
Skewness9.9499945
Sum1.1275308 × 109
Variance4.8189257 × 108
MonotonicityNot monotonic
2026-01-19T10:07:35.286383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 341
 
0.5%
5817 12
 
< 0.1%
11622 12
 
< 0.1%
3933 12
 
< 0.1%
10428 11
 
< 0.1%
5426 11
 
< 0.1%
10349 11
 
< 0.1%
7373 11
 
< 0.1%
6427 11
 
< 0.1%
7236 10
 
< 0.1%
Other values (31341) 67379
99.3%
ValueCountFrequency (%)
0 341
0.5%
1 4
 
< 0.1%
2 5
 
< 0.1%
3 2
 
< 0.1%
4 8
 
< 0.1%
5 5
 
< 0.1%
6 2
 
< 0.1%
7 4
 
< 0.1%
8 5
 
< 0.1%
9 5
 
< 0.1%
ValueCountFrequency (%)
1101954 1
< 0.1%
971736 1
< 0.1%
799950 1
< 0.1%
664894 1
< 0.1%
659947 1
< 0.1%
566420 1
< 0.1%
486649 1
< 0.1%
484549 1
< 0.1%
477970 1
< 0.1%
454191 1
< 0.1%

revol_util
Real number (ℝ)

High correlation 

Distinct1073
Distinct (%)1.6%
Missing46
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean50.465264
Minimum0
Maximum137.9
Zeros364
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:35.367001image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.5
Q131.7
median50.4
Q369.5
95-th percentile91.2
Maximum137.9
Range137.9
Interquartile range (IQR)37.8

Descriptive statistics

Standard deviation24.742038
Coefficient of variation (CV)0.49027858
Kurtosis-0.83482428
Mean50.465264
Median Absolute Deviation (MAD)18.9
Skewness-0.0049774896
Sum3420283.3
Variance612.16844
MonotonicityNot monotonic
2026-01-19T10:07:35.447203image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 364
 
0.5%
57 147
 
0.2%
45 138
 
0.2%
61 135
 
0.2%
48 133
 
0.2%
55 133
 
0.2%
44 133
 
0.2%
60 132
 
0.2%
39 130
 
0.2%
46 127
 
0.2%
Other values (1063) 66203
97.6%
ValueCountFrequency (%)
0 364
0.5%
0.1 46
 
0.1%
0.12 1
 
< 0.1%
0.2 41
 
0.1%
0.3 27
 
< 0.1%
0.4 22
 
< 0.1%
0.5 36
 
0.1%
0.6 32
 
< 0.1%
0.7 26
 
< 0.1%
0.8 28
 
< 0.1%
ValueCountFrequency (%)
137.9 1
< 0.1%
133.6 1
< 0.1%
129.4 1
< 0.1%
128.7 1
< 0.1%
127.6 2
< 0.1%
115.7 2
< 0.1%
114.8 1
< 0.1%
113.8 1
< 0.1%
113.7 1
< 0.1%
113.1 1
< 0.1%

total_acc
Real number (ℝ)

High correlation 

Distinct107
Distinct (%)0.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean24.216264
Minimum1
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:35.527732image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q115
median22
Q331
95-th percentile47
Maximum165
Range164
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.069215
Coefficient of variation (CV)0.49839295
Kurtosis2.3137989
Mean24.216264
Median Absolute Deviation (MAD)8
Skewness1.0554072
Sum1642347
Variance145.66595
MonotonicityNot monotonic
2026-01-19T10:07:35.607134image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 2518
 
3.7%
18 2472
 
3.6%
20 2470
 
3.6%
19 2442
 
3.6%
22 2409
 
3.6%
17 2404
 
3.5%
23 2396
 
3.5%
15 2360
 
3.5%
16 2342
 
3.5%
24 2263
 
3.3%
Other values (97) 43744
64.5%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 43
 
0.1%
3 132
 
0.2%
4 305
 
0.4%
5 477
 
0.7%
6 712
1.0%
7 959
1.4%
8 1178
1.7%
9 1416
2.1%
10 1528
2.3%
ValueCountFrequency (%)
165 1
< 0.1%
160 1
< 0.1%
144 1
< 0.1%
133 1
< 0.1%
116 1
< 0.1%
112 1
< 0.1%
111 1
< 0.1%
101 1
< 0.1%
99 1
< 0.1%
98 1
< 0.1%

initial_list_status
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
w
46039 
f
21782 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters67821
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowf
2nd roww
3rd rowf
4th rowf
5th roww

Common Values

ValueCountFrequency (%)
w 46039
67.9%
f 21782
32.1%

Length

2026-01-19T10:07:35.682764image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:35.740377image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
w 46039
67.9%
f 21782
32.1%

Most occurring characters

ValueCountFrequency (%)
w 46039
67.9%
f 21782
32.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
w 46039
67.9%
f 21782
32.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
w 46039
67.9%
f 21782
32.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
w 46039
67.9%
f 21782
32.1%

out_prncp
Real number (ℝ)

High correlation  Zeros 

Distinct22587
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4191.1591
Minimum0
Maximum39318.12
Zeros40642
Zeros (%)59.9%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:35.804540image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36042.64
95-th percentile21072.04
Maximum39318.12
Range39318.12
Interquartile range (IQR)6042.64

Descriptive statistics

Standard deviation7329.4412
Coefficient of variation (CV)1.7487862
Kurtosis4.0209917
Mean4191.1591
Median Absolute Deviation (MAD)0
Skewness2.0740616
Sum2.842486 × 108
Variance53720709
MonotonicityNot monotonic
2026-01-19T10:07:36.008899image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40642
59.9%
8747.25 11
 
< 0.1%
9238.49 10
 
< 0.1%
7705.1 10
 
< 0.1%
8784.5 9
 
< 0.1%
30587.85 9
 
< 0.1%
8457.66 9
 
< 0.1%
8808.53 9
 
< 0.1%
9070.32 9
 
< 0.1%
6725.76 9
 
< 0.1%
Other values (22577) 27094
39.9%
ValueCountFrequency (%)
0 40642
59.9%
0.03 1
 
< 0.1%
0.13 1
 
< 0.1%
0.18 2
 
< 0.1%
0.29 1
 
< 0.1%
0.34 1
 
< 0.1%
0.37 1
 
< 0.1%
0.4 1
 
< 0.1%
0.41 1
 
< 0.1%
0.46 1
 
< 0.1%
ValueCountFrequency (%)
39318.12 1
 
< 0.1%
39257.67 1
 
< 0.1%
39136.96 1
 
< 0.1%
39055.41 1
 
< 0.1%
39040.73 1
 
< 0.1%
39010.32 1
 
< 0.1%
38766.44 1
 
< 0.1%
38669.13 1
 
< 0.1%
38608.83 1
 
< 0.1%
38553.3 3
< 0.1%

out_prncp_inv
Real number (ℝ)

High correlation  Zeros 

Distinct22824
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4190.2138
Minimum0
Maximum39318.12
Zeros40642
Zeros (%)59.9%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:36.092867image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36035.36
95-th percentile21070.39
Maximum39318.12
Range39318.12
Interquartile range (IQR)6035.36

Descriptive statistics

Standard deviation7328.5608
Coefficient of variation (CV)1.7489706
Kurtosis4.0230643
Mean4190.2138
Median Absolute Deviation (MAD)0
Skewness2.0744797
Sum2.8418449 × 108
Variance53707803
MonotonicityNot monotonic
2026-01-19T10:07:36.175240image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40642
59.9%
8747.25 11
 
< 0.1%
7705.1 10
 
< 0.1%
9238.49 10
 
< 0.1%
8457.66 9
 
< 0.1%
6172.91 9
 
< 0.1%
16392.01 9
 
< 0.1%
8757.61 8
 
< 0.1%
30587.85 8
 
< 0.1%
2996.63 8
 
< 0.1%
Other values (22814) 27097
40.0%
ValueCountFrequency (%)
0 40642
59.9%
0.03 1
 
< 0.1%
0.13 1
 
< 0.1%
0.18 2
 
< 0.1%
0.29 1
 
< 0.1%
0.34 1
 
< 0.1%
0.37 1
 
< 0.1%
0.4 1
 
< 0.1%
0.41 1
 
< 0.1%
0.46 1
 
< 0.1%
ValueCountFrequency (%)
39318.12 1
 
< 0.1%
39257.67 1
 
< 0.1%
39136.96 1
 
< 0.1%
39055.41 1
 
< 0.1%
39040.73 1
 
< 0.1%
39010.32 1
 
< 0.1%
38766.44 1
 
< 0.1%
38669.13 1
 
< 0.1%
38608.83 1
 
< 0.1%
38553.3 3
< 0.1%

total_pymnt
Real number (ℝ)

High correlation 

Distinct64798
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12123.252
Minimum0
Maximum62687.031
Zeros27
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:36.254924image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1363.25
Q14546.75
median9412.282
Q317022.552
95-th percentile32765.2
Maximum62687.031
Range62687.031
Interquartile range (IQR)12475.802

Descriptive statistics

Standard deviation9904.4306
Coefficient of variation (CV)0.81697803
Kurtosis1.3371219
Mean12123.252
Median Absolute Deviation (MAD)5683.4518
Skewness1.2598179
Sum8.2221107 × 108
Variance98097745
MonotonicityNot monotonic
2026-01-19T10:07:36.334906image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27
 
< 0.1%
27095.91178 9
 
< 0.1%
10838.35484 8
 
< 0.1%
915.34 8
 
< 0.1%
4185.03 8
 
< 0.1%
9737.46 7
 
< 0.1%
13510.12859 7
 
< 0.1%
5791.27 7
 
< 0.1%
2765.74 7
 
< 0.1%
2881.07 7
 
< 0.1%
Other values (64788) 67726
99.9%
ValueCountFrequency (%)
0 27
< 0.1%
33.63 1
 
< 0.1%
93.83 1
 
< 0.1%
102.83 1
 
< 0.1%
107.42 2
 
< 0.1%
110.28 2
 
< 0.1%
113.29 1
 
< 0.1%
113.59 1
 
< 0.1%
117.05 1
 
< 0.1%
121.82 1
 
< 0.1%
ValueCountFrequency (%)
62687.03089 1
< 0.1%
62070.70453 1
< 0.1%
60576.30682 1
< 0.1%
60336.05294 1
< 0.1%
60197.48715 1
< 0.1%
59807.61598 1
< 0.1%
59702.84173 1
< 0.1%
59683.79981 1
< 0.1%
59534.6569 1
< 0.1%
59068.97352 1
< 0.1%

total_pymnt_inv
Real number (ℝ)

High correlation 

Distinct63817
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12106.854
Minimum0
Maximum62687.03
Zeros32
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:36.413452image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1354.48
Q14532.36
median9397.7
Q317005.04
95-th percentile32745.62
Maximum62687.03
Range62687.03
Interquartile range (IQR)12472.68

Descriptive statistics

Standard deviation9901.3022
Coefficient of variation (CV)0.81782616
Kurtosis1.3404702
Mean12106.854
Median Absolute Deviation (MAD)5680.49
Skewness1.2608413
Sum8.2109897 × 108
Variance98035786
MonotonicityNot monotonic
2026-01-19T10:07:36.490773image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32
 
< 0.1%
10956.78 12
 
< 0.1%
11784.23 11
 
< 0.1%
11431.12 11
 
< 0.1%
11977.77 9
 
< 0.1%
27095.91 9
 
< 0.1%
915.34 8
 
< 0.1%
21913.55 8
 
< 0.1%
11258.44 8
 
< 0.1%
26296.28 8
 
< 0.1%
Other values (63807) 67705
99.8%
ValueCountFrequency (%)
0 32
< 0.1%
33.63 1
 
< 0.1%
64.03 1
 
< 0.1%
89.69 1
 
< 0.1%
90.6 1
 
< 0.1%
91.48 1
 
< 0.1%
100.89 1
 
< 0.1%
107.42 2
 
< 0.1%
110.28 2
 
< 0.1%
111.22 1
 
< 0.1%
ValueCountFrequency (%)
62687.03 1
< 0.1%
62026.37 1
< 0.1%
60576.31 1
< 0.1%
60336.05 1
< 0.1%
60197.49 1
< 0.1%
59702.84 1
< 0.1%
59683.8 1
< 0.1%
59679.46 1
< 0.1%
59403.14 1
< 0.1%
59068.97 1
< 0.1%

total_rec_prncp
Real number (ℝ)

High correlation 

Distinct31445
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9539.3143
Minimum0
Maximum40000
Zeros69
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:36.571928image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile833.31
Q13001.14
median7000
Q314000
95-th percentile27991.2
Maximum40000
Range40000
Interquartile range (IQR)10998.86

Descriptive statistics

Standard deviation8339.4348
Coefficient of variation (CV)0.87421743
Kurtosis1.0963309
Mean9539.3143
Median Absolute Deviation (MAD)4721.66
Skewness1.250031
Sum6.4696583 × 108
Variance69546172
MonotonicityNot monotonic
2026-01-19T10:07:36.656795image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 2376
 
3.5%
12000 1772
 
2.6%
15000 1742
 
2.6%
20000 1698
 
2.5%
35000 1185
 
1.7%
6000 1177
 
1.7%
5000 1162
 
1.7%
8000 1149
 
1.7%
16000 873
 
1.3%
25000 801
 
1.2%
Other values (31435) 53886
79.5%
ValueCountFrequency (%)
0 69
0.1%
23.97 1
 
< 0.1%
30.32 1
 
< 0.1%
30.56 1
 
< 0.1%
41.26 1
 
< 0.1%
43.28 1
 
< 0.1%
46.44 1
 
< 0.1%
52.38 1
 
< 0.1%
54.82 1
 
< 0.1%
62.62 2
 
< 0.1%
ValueCountFrequency (%)
40000 156
0.2%
39850 1
 
< 0.1%
39775 2
 
< 0.1%
39500 1
 
< 0.1%
39350 1
 
< 0.1%
39000 2
 
< 0.1%
38756.91 2
 
< 0.1%
38724.46 1
 
< 0.1%
38640.37 1
 
< 0.1%
38594.08 1
 
< 0.1%

total_rec_int
Real number (ℝ)

High correlation 

Distinct60472
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2439.0198
Minimum0
Maximum27687.03
Zeros73
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:36.736199image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile201.24
Q1733.3
median1535.52
Q33128.69
95-th percentile7816.73
Maximum27687.03
Range27687.03
Interquartile range (IQR)2395.39

Descriptive statistics

Standard deviation2671.7501
Coefficient of variation (CV)1.0954196
Kurtosis8.9189387
Mean2439.0198
Median Absolute Deviation (MAD)985.46
Skewness2.5156041
Sum1.6541676 × 108
Variance7138248.4
MonotonicityNot monotonic
2026-01-19T10:07:36.814049image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 73
 
0.1%
1784.23 14
 
< 0.1%
956.78 13
 
< 0.1%
1431.12 13
 
< 0.1%
1977.77 12
 
< 0.1%
2095.91 9
 
< 0.1%
1809.76 9
 
< 0.1%
838.35 9
 
< 0.1%
2862.28 9
 
< 0.1%
1257.53 8
 
< 0.1%
Other values (60462) 67652
99.8%
ValueCountFrequency (%)
0 73
0.1%
0.25 1
 
< 0.1%
0.55 2
 
< 0.1%
0.66 1
 
< 0.1%
0.89 1
 
< 0.1%
0.91 1
 
< 0.1%
0.92 1
 
< 0.1%
0.94 1
 
< 0.1%
0.95 1
 
< 0.1%
0.99 1
 
< 0.1%
ValueCountFrequency (%)
27687.03 1
< 0.1%
27236.97 1
< 0.1%
27070.7 1
< 0.1%
25950.98 1
< 0.1%
25576.31 1
< 0.1%
25536.61 1
< 0.1%
25336.05 1
< 0.1%
25197.49 1
< 0.1%
24805.34 1
< 0.1%
24757.65 1
< 0.1%

total_rec_late_fee
Real number (ℝ)

Zeros 

Distinct1501
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4477943
Minimum-2 × 10-9
Maximum584.7
Zeros65248
Zeros (%)96.2%
Negative1
Negative (%)< 0.1%
Memory size1.0 MiB
2026-01-19T10:07:36.888696image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-2 × 10-9
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum584.7
Range584.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.115548
Coefficient of variation (CV)7.677574
Kurtosis618.77552
Mean1.4477943
Median Absolute Deviation (MAD)0
Skewness19.158227
Sum98190.856
Variance123.5554
MonotonicityNot monotonic
2026-01-19T10:07:36.969337image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65248
96.2%
15 590
 
0.9%
30 124
 
0.2%
45 37
 
0.1%
60 18
 
< 0.1%
75 6
 
< 0.1%
16.49 6
 
< 0.1%
16.37 6
 
< 0.1%
90 5
 
< 0.1%
15.94 5
 
< 0.1%
Other values (1491) 1776
 
2.6%
ValueCountFrequency (%)
-2 × 10-91
 
< 0.1%
0 65248
96.2%
0.01 1
 
< 0.1%
1.88 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
11.48 1
 
< 0.1%
14.645 1
 
< 0.1%
14.91605558 1
 
< 0.1%
ValueCountFrequency (%)
584.7 1
< 0.1%
571.4 1
< 0.1%
525.2 1
< 0.1%
492.31 1
< 0.1%
457.82 1
< 0.1%
427.14 1
< 0.1%
411.12 1
< 0.1%
367.05 1
< 0.1%
354.92 1
< 0.1%
352.07 1
< 0.1%

recoveries
Real number (ℝ)

High correlation  Zeros 

Distinct5386
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143.47013
Minimum0
Maximum25346.1
Zeros62171
Zeros (%)91.7%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:37.049282image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile925.49
Maximum25346.1
Range25346.1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation728.95388
Coefficient of variation (CV)5.0808757
Kurtosis164.45736
Mean143.47013
Median Absolute Deviation (MAD)0
Skewness10.030248
Sum9730287.5
Variance531373.76
MonotonicityNot monotonic
2026-01-19T10:07:37.129065image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 62171
91.7%
50 23
 
< 0.1%
100 19
 
< 0.1%
150 13
 
< 0.1%
200 13
 
< 0.1%
75 12
 
< 0.1%
600 11
 
< 0.1%
400 9
 
< 0.1%
350 7
 
< 0.1%
175 6
 
< 0.1%
Other values (5376) 5537
 
8.2%
ValueCountFrequency (%)
0 62171
91.7%
0.03 1
 
< 0.1%
0.04 2
 
< 0.1%
0.06 3
 
< 0.1%
0.08 1
 
< 0.1%
0.09 2
 
< 0.1%
0.1 3
 
< 0.1%
0.11 1
 
< 0.1%
0.12 2
 
< 0.1%
0.16 2
 
< 0.1%
ValueCountFrequency (%)
25346.1 1
< 0.1%
23194.48 1
< 0.1%
21493.26 1
< 0.1%
19892.11 1
< 0.1%
17516.34 1
< 0.1%
17003.17 1
< 0.1%
16997.13 1
< 0.1%
16886.27 1
< 0.1%
16205.26 1
< 0.1%
16078.46 1
< 0.1%

collection_recovery_fee
Real number (ℝ)

High correlation  Zeros 

Distinct5246
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.772092
Minimum0
Maximum4562.298
Zeros62419
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:37.204930image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile136.611
Maximum4562.298
Range4562.298
Interquartile range (IQR)0

Descriptive statistics

Standard deviation127.36989
Coefficient of variation (CV)5.357959
Kurtosis182.89481
Mean23.772092
Median Absolute Deviation (MAD)0
Skewness10.658839
Sum1612247.1
Variance16223.09
MonotonicityNot monotonic
2026-01-19T10:07:37.284760image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 62419
92.0%
9 18
 
< 0.1%
18 12
 
< 0.1%
27 11
 
< 0.1%
108 10
 
< 0.1%
36 8
 
< 0.1%
13.5 8
 
< 0.1%
63 7
 
< 0.1%
72 7
 
< 0.1%
144 5
 
< 0.1%
Other values (5236) 5316
 
7.8%
ValueCountFrequency (%)
0 62419
92.0%
0.3221 1
 
< 0.1%
0.3353000003 1
 
< 0.1%
0.38 1
 
< 0.1%
0.44 1
 
< 0.1%
0.4547 1
 
< 0.1%
0.55 1
 
< 0.1%
0.57 1
 
< 0.1%
0.6 1
 
< 0.1%
0.62 1
 
< 0.1%
ValueCountFrequency (%)
4562.298 1
< 0.1%
4175.0064 1
< 0.1%
3868.7868 1
< 0.1%
3580.5798 1
< 0.1%
3152.9412 1
< 0.1%
3060.5706 1
< 0.1%
3059.4834 1
< 0.1%
3039.5286 1
< 0.1%
2916.9468 1
< 0.1%
2894.1228 1
< 0.1%
Distinct128
Distinct (%)0.2%
Missing66
Missing (%)0.1%
Memory size1.0 MiB
Minimum2008-02-01 00:00:00
Maximum2019-03-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:37.362890image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:37.449882image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

last_pymnt_amnt
Real number (ℝ)

High correlation 

Distinct43925
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3465.2517
Minimum0
Maximum41095.65
Zeros81
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:37.535074image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100
Q1310.57
median602.37
Q33847.73
95-th percentile17056.89
Maximum41095.65
Range41095.65
Interquartile range (IQR)3537.16

Descriptive statistics

Standard deviation6049.1729
Coefficient of variation (CV)1.7456662
Kurtosis6.8439916
Mean3465.2517
Median Absolute Deviation (MAD)399.96
Skewness2.5336892
Sum2.3501684 × 108
Variance36592493
MonotonicityNot monotonic
2026-01-19T10:07:37.610129image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 111
 
0.2%
0 81
 
0.1%
100 65
 
0.1%
361.38 65
 
0.1%
332.1 63
 
0.1%
301.15 61
 
0.1%
313.23 55
 
0.1%
309.74 50
 
0.1%
320.05 48
 
0.1%
322.35 48
 
0.1%
Other values (43915) 67174
99.0%
ValueCountFrequency (%)
0 81
0.1%
0.01 10
 
< 0.1%
0.02 3
 
< 0.1%
0.03 3
 
< 0.1%
0.04 2
 
< 0.1%
0.05 4
 
< 0.1%
0.06 2
 
< 0.1%
0.07 4
 
< 0.1%
0.08 3
 
< 0.1%
0.09 1
 
< 0.1%
ValueCountFrequency (%)
41095.65 1
< 0.1%
40811.15 1
< 0.1%
40690.5 1
< 0.1%
40642.54 1
< 0.1%
40521.7 1
< 0.1%
40401.94 1
< 0.1%
40377.68 1
< 0.1%
40308.01 1
< 0.1%
40287.2 1
< 0.1%
40266.11 1
< 0.1%

next_pymnt_d
Date

Missing 

Distinct39
Distinct (%)0.1%
Missing40433
Missing (%)59.6%
Memory size1.0 MiB
Minimum2008-12-01 00:00:00
Maximum2019-05-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:37.678475image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:37.753476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
Distinct116
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
Minimum2007-06-01 00:00:00
Maximum2019-03-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:37.836760image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:38.045251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

last_fico_range_high
Real number (ℝ)

High correlation 

Distinct72
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean687.46727
Minimum0
Maximum850
Zeros7
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:38.130010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile534
Q1654
median699
Q3734
95-th percentile794
Maximum850
Range850
Interquartile range (IQR)80

Descriptive statistics

Standard deviation73.262444
Coefficient of variation (CV)0.10656863
Kurtosis0.88669788
Mean687.46727
Median Absolute Deviation (MAD)40
Skewness-0.75987978
Sum46624718
Variance5367.3857
MonotonicityNot monotonic
2026-01-19T10:07:38.205066image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
694 2499
 
3.7%
709 2459
 
3.6%
699 2448
 
3.6%
719 2385
 
3.5%
714 2384
 
3.5%
704 2375
 
3.5%
684 2319
 
3.4%
689 2300
 
3.4%
724 2278
 
3.4%
679 2153
 
3.2%
Other values (62) 44221
65.2%
ValueCountFrequency (%)
0 7
 
< 0.1%
499 1112
1.6%
504 271
 
0.4%
509 287
 
0.4%
514 317
 
0.5%
519 325
 
0.5%
524 373
 
0.5%
529 383
 
0.6%
534 376
 
0.6%
539 416
 
0.6%
ValueCountFrequency (%)
850 17
 
< 0.1%
844 19
 
< 0.1%
839 53
 
0.1%
834 106
 
0.2%
829 164
 
0.2%
824 204
 
0.3%
819 294
0.4%
814 403
0.6%
809 478
0.7%
804 583
0.9%

last_fico_range_low
Real number (ℝ)

High correlation  Zeros 

Distinct71
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean675.35137
Minimum0
Maximum845
Zeros1119
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:38.281289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile530
Q1650
median695
Q3730
95-th percentile790
Maximum845
Range845
Interquartile range (IQR)80

Descriptive statistics

Standard deviation111.25491
Coefficient of variation (CV)0.16473634
Kurtosis19.82994
Mean675.35137
Median Absolute Deviation (MAD)40
Skewness-3.7191305
Sum45803005
Variance12377.656
MonotonicityNot monotonic
2026-01-19T10:07:38.356723image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
690 2499
 
3.7%
705 2459
 
3.6%
695 2448
 
3.6%
715 2385
 
3.5%
710 2384
 
3.5%
700 2375
 
3.5%
680 2319
 
3.4%
685 2300
 
3.4%
720 2278
 
3.4%
675 2153
 
3.2%
Other values (61) 44221
65.2%
ValueCountFrequency (%)
0 1119
1.6%
500 271
 
0.4%
505 287
 
0.4%
510 317
 
0.5%
515 325
 
0.5%
520 373
 
0.5%
525 383
 
0.6%
530 376
 
0.6%
535 416
 
0.6%
540 427
 
0.6%
ValueCountFrequency (%)
845 17
 
< 0.1%
840 19
 
< 0.1%
835 53
 
0.1%
830 106
 
0.2%
825 164
 
0.2%
820 204
 
0.3%
815 294
0.4%
810 403
0.6%
805 478
0.7%
800 583
0.9%

collections_12_mths_ex_med
Real number (ℝ)

Zeros 

Distinct7
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.018240802
Minimum0
Maximum6
Zeros66688
Zeros (%)98.3%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:38.418813image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.15159498
Coefficient of variation (CV)8.3107628
Kurtosis239.39851
Mean0.018240802
Median Absolute Deviation (MAD)0
Skewness11.908474
Sum1237
Variance0.022981038
MonotonicityNot monotonic
2026-01-19T10:07:38.477082image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 66688
98.3%
1 1051
 
1.5%
2 58
 
0.1%
3 11
 
< 0.1%
6 3
 
< 0.1%
5 3
 
< 0.1%
4 1
 
< 0.1%
(Missing) 6
 
< 0.1%
ValueCountFrequency (%)
0 66688
98.3%
1 1051
 
1.5%
2 58
 
0.1%
3 11
 
< 0.1%
4 1
 
< 0.1%
5 3
 
< 0.1%
6 3
 
< 0.1%
ValueCountFrequency (%)
6 3
 
< 0.1%
5 3
 
< 0.1%
4 1
 
< 0.1%
3 11
 
< 0.1%
2 58
 
0.1%
1 1051
 
1.5%
0 66688
98.3%

mths_since_last_major_derog
Real number (ℝ)

High correlation  Missing 

Distinct125
Distinct (%)0.7%
Missing50351
Missing (%)74.2%
Infinite0
Infinite (%)0.0%
Mean44.325758
Minimum0
Maximum155
Zeros10
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:38.547703image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q127
median44
Q362
95-th percentile77
Maximum155
Range155
Interquartile range (IQR)35

Descriptive statistics

Standard deviation21.478716
Coefficient of variation (CV)0.4845651
Kurtosis-0.72618836
Mean44.325758
Median Absolute Deviation (MAD)17
Skewness0.036649102
Sum774371
Variance461.33523
MonotonicityNot monotonic
2026-01-19T10:07:38.629988image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 287
 
0.4%
36 285
 
0.4%
47 285
 
0.4%
40 281
 
0.4%
42 279
 
0.4%
46 276
 
0.4%
44 273
 
0.4%
48 272
 
0.4%
45 270
 
0.4%
29 264
 
0.4%
Other values (115) 14698
 
21.7%
(Missing) 50351
74.2%
ValueCountFrequency (%)
0 10
 
< 0.1%
1 42
 
0.1%
2 39
 
0.1%
3 66
0.1%
4 93
0.1%
5 101
0.1%
6 125
0.2%
7 122
0.2%
8 126
0.2%
9 130
0.2%
ValueCountFrequency (%)
155 1
 
< 0.1%
146 1
 
< 0.1%
140 1
 
< 0.1%
130 1
 
< 0.1%
126 1
 
< 0.1%
125 1
 
< 0.1%
124 1
 
< 0.1%
123 1
 
< 0.1%
120 3
< 0.1%
118 3
< 0.1%

policy_code
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
1.0
67821 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters203463
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 67821
100.0%

Length

2026-01-19T10:07:38.709019image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:38.765012image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
1.0 67821
100.0%

Most occurring characters

ValueCountFrequency (%)
1 67821
33.3%
. 67821
33.3%
0 67821
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 203463
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 67821
33.3%
. 67821
33.3%
0 67821
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 203463
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 67821
33.3%
. 67821
33.3%
0 67821
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 203463
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 67821
33.3%
. 67821
33.3%
0 67821
33.3%

application_type
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
Individual
64214 
Joint App
 
3607

Length

Max length10
Median length10
Mean length9.9468159
Min length9

Characters and Unicode

Total characters674603
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIndividual
2nd rowIndividual
3rd rowIndividual
4th rowIndividual
5th rowIndividual

Common Values

ValueCountFrequency (%)
Individual 64214
94.7%
Joint App 3607
 
5.3%

Length

2026-01-19T10:07:38.822692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:38.880957image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
individual 64214
89.9%
joint 3607
 
5.0%
app 3607
 
5.0%

Most occurring characters

ValueCountFrequency (%)
i 132035
19.6%
d 128428
19.0%
n 67821
10.1%
I 64214
9.5%
v 64214
9.5%
u 64214
9.5%
a 64214
9.5%
l 64214
9.5%
p 7214
 
1.1%
J 3607
 
0.5%
Other values (4) 14428
 
2.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 674603
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 132035
19.6%
d 128428
19.0%
n 67821
10.1%
I 64214
9.5%
v 64214
9.5%
u 64214
9.5%
a 64214
9.5%
l 64214
9.5%
p 7214
 
1.1%
J 3607
 
0.5%
Other values (4) 14428
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 674603
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 132035
19.6%
d 128428
19.0%
n 67821
10.1%
I 64214
9.5%
v 64214
9.5%
u 64214
9.5%
a 64214
9.5%
l 64214
9.5%
p 7214
 
1.1%
J 3607
 
0.5%
Other values (4) 14428
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 674603
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 132035
19.6%
d 128428
19.0%
n 67821
10.1%
I 64214
9.5%
v 64214
9.5%
u 64214
9.5%
a 64214
9.5%
l 64214
9.5%
p 7214
 
1.1%
J 3607
 
0.5%
Other values (4) 14428
 
2.1%

annual_inc_joint
Real number (ℝ)

High correlation  Missing 

Distinct1093
Distinct (%)30.3%
Missing64214
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean123258.77
Minimum16440
Maximum1161498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:38.945820image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum16440
5-th percentile54000
Q182003.25
median111000
Q3148000
95-th percentile229669.2
Maximum1161498
Range1145058
Interquartile range (IQR)65996.75

Descriptive statistics

Standard deviation65968.497
Coefficient of variation (CV)0.53520325
Kurtosis31.233392
Mean123258.77
Median Absolute Deviation (MAD)31000
Skewness3.5850769
Sum4.445944 × 108
Variance4.3518426 × 109
MonotonicityNot monotonic
2026-01-19T10:07:39.033847image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110000 65
 
0.1%
100000 63
 
0.1%
120000 60
 
0.1%
150000 54
 
0.1%
90000 52
 
0.1%
80000 51
 
0.1%
115000 47
 
0.1%
140000 46
 
0.1%
130000 45
 
0.1%
135000 44
 
0.1%
Other values (1083) 3080
 
4.5%
(Missing) 64214
94.7%
ValueCountFrequency (%)
16440 1
< 0.1%
23000 1
< 0.1%
26500 1
< 0.1%
27288 1
< 0.1%
28680 1
< 0.1%
29000 1
< 0.1%
30000 1
< 0.1%
30800 1
< 0.1%
30966 1
< 0.1%
31324 1
< 0.1%
ValueCountFrequency (%)
1161498 1
< 0.1%
850000 1
< 0.1%
775000 1
< 0.1%
686000 1
< 0.1%
660000 1
< 0.1%
610628 1
< 0.1%
593000 1
< 0.1%
540000 1
< 0.1%
538000 1
< 0.1%
528000 1
< 0.1%

dti_joint
Real number (ℝ)

High correlation  Missing 

Distinct2101
Distinct (%)58.2%
Missing64214
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean19.230865
Minimum0.34
Maximum41.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:39.113379image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.34
5-th percentile7.363
Q113.16
median18.76
Q324.69
95-th percentile33.231
Maximum41.5
Range41.16
Interquartile range (IQR)11.53

Descriptive statistics

Standard deviation7.9156517
Coefficient of variation (CV)0.41161184
Kurtosis-0.51401102
Mean19.230865
Median Absolute Deviation (MAD)5.72
Skewness0.25383991
Sum69365.73
Variance62.657542
MonotonicityNot monotonic
2026-01-19T10:07:39.188865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17.4 7
 
< 0.1%
20.07 7
 
< 0.1%
9.41 6
 
< 0.1%
14.79 6
 
< 0.1%
21.56 6
 
< 0.1%
23.21 6
 
< 0.1%
16.47 6
 
< 0.1%
12.39 5
 
< 0.1%
25.09 5
 
< 0.1%
15.66 5
 
< 0.1%
Other values (2091) 3548
 
5.2%
(Missing) 64214
94.7%
ValueCountFrequency (%)
0.34 1
< 0.1%
0.37 1
< 0.1%
0.43 1
< 0.1%
0.65 1
< 0.1%
0.87 1
< 0.1%
0.94 1
< 0.1%
0.97 1
< 0.1%
1.11 1
< 0.1%
1.12 1
< 0.1%
1.14 1
< 0.1%
ValueCountFrequency (%)
41.5 1
< 0.1%
39.73 1
< 0.1%
39.64 2
< 0.1%
39.53 2
< 0.1%
39.52 1
< 0.1%
39.51 1
< 0.1%
39.35 1
< 0.1%
39.29 1
< 0.1%
39.28 1
< 0.1%
39.26 1
< 0.1%

verification_status_joint
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.1%
Missing64357
Missing (%)94.9%
Memory size1.0 MiB
Not Verified
1742 
Source Verified
1026 
Verified
696 

Length

Max length15
Median length12
Mean length12.084873
Min length8

Characters and Unicode

Total characters41862
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSource Verified
2nd rowNot Verified
3rd rowNot Verified
4th rowNot Verified
5th rowVerified

Common Values

ValueCountFrequency (%)
Not Verified 1742
 
2.6%
Source Verified 1026
 
1.5%
Verified 696
 
1.0%
(Missing) 64357
94.9%

Length

2026-01-19T10:07:39.266072image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:39.328577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
verified 3464
55.6%
not 1742
28.0%
source 1026
 
16.5%

Most occurring characters

ValueCountFrequency (%)
e 7954
19.0%
i 6928
16.5%
r 4490
10.7%
f 3464
8.3%
V 3464
8.3%
d 3464
8.3%
2768
 
6.6%
o 2768
 
6.6%
N 1742
 
4.2%
t 1742
 
4.2%
Other values (3) 3078
 
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41862
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 7954
19.0%
i 6928
16.5%
r 4490
10.7%
f 3464
8.3%
V 3464
8.3%
d 3464
8.3%
2768
 
6.6%
o 2768
 
6.6%
N 1742
 
4.2%
t 1742
 
4.2%
Other values (3) 3078
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41862
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 7954
19.0%
i 6928
16.5%
r 4490
10.7%
f 3464
8.3%
V 3464
8.3%
d 3464
8.3%
2768
 
6.6%
o 2768
 
6.6%
N 1742
 
4.2%
t 1742
 
4.2%
Other values (3) 3078
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41862
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 7954
19.0%
i 6928
16.5%
r 4490
10.7%
f 3464
8.3%
V 3464
8.3%
d 3464
8.3%
2768
 
6.6%
o 2768
 
6.6%
N 1742
 
4.2%
t 1742
 
4.2%
Other values (3) 3078
 
7.4%

acc_now_delinq
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct6
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.0038779121
Minimum0
Maximum5
Zeros67579
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:39.386511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.069329786
Coefficient of variation (CV)17.878122
Kurtosis882.01594
Mean0.0038779121
Median Absolute Deviation (MAD)0
Skewness23.947633
Sum263
Variance0.0048066192
MonotonicityNot monotonic
2026-01-19T10:07:39.448658image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 67579
99.6%
1 225
 
0.3%
2 13
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
0 67579
99.6%
1 225
 
0.3%
2 13
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
2 13
 
< 0.1%
1 225
 
0.3%
0 67579
99.6%

tot_coll_amt
Real number (ℝ)

High correlation  Missing  Skewed  Zeros 

Distinct3039
Distinct (%)4.6%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean226.97386
Minimum0
Maximum262740
Zeros55687
Zeros (%)82.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:39.520447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile795.65
Maximum262740
Range262740
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2075.5714
Coefficient of variation (CV)9.1445395
Kurtosis5600.7342
Mean226.97386
Median Absolute Deviation (MAD)0
Skewness56.804743
Sum14918538
Variance4307996.8
MonotonicityNot monotonic
2026-01-19T10:07:39.605573image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 55687
82.1%
50 108
 
0.2%
100 106
 
0.2%
150 74
 
0.1%
75 65
 
0.1%
60 61
 
0.1%
200 53
 
0.1%
80 43
 
0.1%
65 42
 
0.1%
55 39
 
0.1%
Other values (3029) 9450
 
13.9%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 55687
82.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
13 1
 
< 0.1%
14 2
 
< 0.1%
16 1
 
< 0.1%
21 1
 
< 0.1%
23 2
 
< 0.1%
24 1
 
< 0.1%
25 8
 
< 0.1%
ValueCountFrequency (%)
262740 1
< 0.1%
195200 1
< 0.1%
122848 1
< 0.1%
114407 1
< 0.1%
102327 1
< 0.1%
66704 1
< 0.1%
62380 1
< 0.1%
60531 1
< 0.1%
59329 1
< 0.1%
55513 1
< 0.1%

tot_cur_bal
Real number (ℝ)

High correlation  Missing 

Distinct57548
Distinct (%)87.6%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean143098.92
Minimum0
Maximum4170862
Zeros32
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:39.686133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8331.35
Q129185
median80002
Q3213679
95-th percentile443971.3
Maximum4170862
Range4170862
Interquartile range (IQR)184494

Descriptive statistics

Standard deviation161274.17
Coefficient of variation (CV)1.1270118
Kurtosis21.799191
Mean143098.92
Median Absolute Deviation (MAD)63464
Skewness2.8151163
Sum9.4056061 × 109
Variance2.6009359 × 1010
MonotonicityNot monotonic
2026-01-19T10:07:39.764489image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32
 
< 0.1%
32298 5
 
< 0.1%
7704 5
 
< 0.1%
23210 5
 
< 0.1%
12325 5
 
< 0.1%
20084 5
 
< 0.1%
19035 5
 
< 0.1%
39438 5
 
< 0.1%
23587 5
 
< 0.1%
21231 5
 
< 0.1%
Other values (57538) 65651
96.8%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 32
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
9 3
 
< 0.1%
17 1
 
< 0.1%
27 1
 
< 0.1%
38 1
 
< 0.1%
41 1
 
< 0.1%
52 1
 
< 0.1%
ValueCountFrequency (%)
4170862 1
< 0.1%
3566850 1
< 0.1%
2485088 1
< 0.1%
2484676 1
< 0.1%
2474878 1
< 0.1%
2471713 1
< 0.1%
2229433 1
< 0.1%
2227024 1
< 0.1%
2216567 1
< 0.1%
2207912 1
< 0.1%

open_acc_6m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct13
Distinct (%)< 0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean0.93994166
Minimum0
Maximum12
Zeros18783
Zeros (%)27.7%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:39.829368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1454542
Coefficient of variation (CV)1.2186439
Kurtosis4.3238029
Mean0.93994166
Median Absolute Deviation (MAD)1
Skewness1.6685464
Sum39314
Variance1.3120654
MonotonicityNot monotonic
2026-01-19T10:07:39.897076image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 18783
27.7%
1 12993
19.2%
2 6136
 
9.0%
3 2469
 
3.6%
4 930
 
1.4%
5 309
 
0.5%
6 126
 
0.2%
7 45
 
0.1%
8 22
 
< 0.1%
9 7
 
< 0.1%
Other values (3) 6
 
< 0.1%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 18783
27.7%
1 12993
19.2%
2 6136
 
9.0%
3 2469
 
3.6%
4 930
 
1.4%
5 309
 
0.5%
6 126
 
0.2%
7 45
 
0.1%
8 22
 
< 0.1%
9 7
 
< 0.1%
ValueCountFrequency (%)
12 2
 
< 0.1%
11 3
 
< 0.1%
10 1
 
< 0.1%
9 7
 
< 0.1%
8 22
 
< 0.1%
7 45
 
0.1%
6 126
 
0.2%
5 309
 
0.5%
4 930
 
1.4%
3 2469
3.6%

open_act_il
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct37
Distinct (%)0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean2.7884808
Minimum0
Maximum56
Zeros4891
Zeros (%)7.2%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:39.963798image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile9
Maximum56
Range56
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.0189269
Coefficient of variation (CV)1.0826422
Kurtosis15.212436
Mean2.7884808
Median Absolute Deviation (MAD)1
Skewness3.0586821
Sum116631
Variance9.1139197
MonotonicityNot monotonic
2026-01-19T10:07:40.033615image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 10736
15.8%
2 10007
 
14.8%
3 6259
 
9.2%
0 4891
 
7.2%
4 3432
 
5.1%
5 1941
 
2.9%
6 1086
 
1.6%
7 749
 
1.1%
8 587
 
0.9%
9 453
 
0.7%
Other values (27) 1685
 
2.5%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 4891
7.2%
1 10736
15.8%
2 10007
14.8%
3 6259
9.2%
4 3432
 
5.1%
5 1941
 
2.9%
6 1086
 
1.6%
7 749
 
1.1%
8 587
 
0.9%
9 453
 
0.7%
ValueCountFrequency (%)
56 1
 
< 0.1%
39 1
 
< 0.1%
34 1
 
< 0.1%
33 1
 
< 0.1%
32 2
 
< 0.1%
31 1
 
< 0.1%
30 4
< 0.1%
29 4
< 0.1%
28 6
< 0.1%
27 6
< 0.1%

open_il_12m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct11
Distinct (%)< 0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean0.68211161
Minimum0
Maximum10
Zeros22734
Zeros (%)33.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:40.101094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.93211745
Coefficient of variation (CV)1.3665175
Kurtosis4.5068052
Mean0.68211161
Median Absolute Deviation (MAD)0
Skewness1.7614864
Sum28530
Variance0.86884294
MonotonicityNot monotonic
2026-01-19T10:07:40.161855image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 22734
33.5%
1 12523
18.5%
2 4593
 
6.8%
3 1376
 
2.0%
4 408
 
0.6%
5 120
 
0.2%
6 51
 
0.1%
7 16
 
< 0.1%
8 3
 
< 0.1%
10 1
 
< 0.1%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 22734
33.5%
1 12523
18.5%
2 4593
 
6.8%
3 1376
 
2.0%
4 408
 
0.6%
5 120
 
0.2%
6 51
 
0.1%
7 16
 
< 0.1%
8 3
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 1
 
< 0.1%
8 3
 
< 0.1%
7 16
 
< 0.1%
6 51
 
0.1%
5 120
 
0.2%
4 408
 
0.6%
3 1376
 
2.0%
2 4593
 
6.8%
1 12523
18.5%

open_il_24m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct19
Distinct (%)< 0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean1.5685698
Minimum0
Maximum22
Zeros11269
Zeros (%)16.6%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:40.224055image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum22
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5915485
Coefficient of variation (CV)1.0146495
Kurtosis6.4835758
Mean1.5685698
Median Absolute Deviation (MAD)1
Skewness1.8203539
Sum65607
Variance2.5330267
MonotonicityNot monotonic
2026-01-19T10:07:40.285098image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 13244
19.5%
0 11269
16.6%
2 8509
 
12.5%
3 4395
 
6.5%
4 2212
 
3.3%
5 1120
 
1.7%
6 526
 
0.8%
7 259
 
0.4%
8 136
 
0.2%
9 61
 
0.1%
Other values (9) 95
 
0.1%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 11269
16.6%
1 13244
19.5%
2 8509
12.5%
3 4395
 
6.5%
4 2212
 
3.3%
5 1120
 
1.7%
6 526
 
0.8%
7 259
 
0.4%
8 136
 
0.2%
9 61
 
0.1%
ValueCountFrequency (%)
22 1
 
< 0.1%
19 2
 
< 0.1%
17 1
 
< 0.1%
15 6
 
< 0.1%
14 5
 
< 0.1%
13 9
 
< 0.1%
12 13
 
< 0.1%
11 16
 
< 0.1%
10 42
0.1%
9 61
0.1%

mths_since_rcnt_il
Real number (ℝ)

High correlation  Missing 

Distinct228
Distinct (%)0.6%
Missing27257
Missing (%)40.2%
Infinite0
Infinite (%)0.0%
Mean21.138546
Minimum0
Maximum402
Zeros21
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:40.357841image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median13
Q324
95-th percentile72
Maximum402
Range402
Interquartile range (IQR)17

Descriptive statistics

Standard deviation25.790341
Coefficient of variation (CV)1.2200622
Kurtosis16.567334
Mean21.138546
Median Absolute Deviation (MAD)8
Skewness3.3830494
Sum857464
Variance665.14171
MonotonicityNot monotonic
2026-01-19T10:07:40.450993image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1822
 
2.7%
7 1806
 
2.7%
4 1800
 
2.7%
6 1760
 
2.6%
5 1718
 
2.5%
8 1703
 
2.5%
9 1656
 
2.4%
11 1522
 
2.2%
10 1514
 
2.2%
13 1504
 
2.2%
Other values (218) 23759
35.0%
(Missing) 27257
40.2%
ValueCountFrequency (%)
0 21
 
< 0.1%
1 889
1.3%
2 1481
2.2%
3 1822
2.7%
4 1800
2.7%
5 1718
2.5%
6 1760
2.6%
7 1806
2.7%
8 1703
2.5%
9 1656
2.4%
ValueCountFrequency (%)
402 1
< 0.1%
330 1
< 0.1%
327 1
< 0.1%
322 1
< 0.1%
320 1
< 0.1%
309 1
< 0.1%
297 1
< 0.1%
284 1
< 0.1%
279 1
< 0.1%
272 1
< 0.1%

total_bal_il
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct29809
Distinct (%)71.3%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean35695.568
Minimum0
Maximum892491
Zeros4674
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:40.531525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18744.25
median23082
Q346329
95-th percentile114036
Maximum892491
Range892491
Interquartile range (IQR)37584.75

Descriptive statistics

Standard deviation44496.779
Coefficient of variation (CV)1.2465631
Kurtosis27.808428
Mean35695.568
Median Absolute Deviation (MAD)17023
Skewness3.7744441
Sum1.4930028 × 109
Variance1.9799633 × 109
MonotonicityNot monotonic
2026-01-19T10:07:40.609107image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4674
 
6.9%
11000 6
 
< 0.1%
9320 5
 
< 0.1%
2375 5
 
< 0.1%
4500 5
 
< 0.1%
11891 5
 
< 0.1%
8150 5
 
< 0.1%
19464 5
 
< 0.1%
1720 5
 
< 0.1%
3781 5
 
< 0.1%
Other values (29799) 37106
54.7%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 4674
6.9%
1 1
 
< 0.1%
16 1
 
< 0.1%
20 1
 
< 0.1%
21 1
 
< 0.1%
23 1
 
< 0.1%
27 1
 
< 0.1%
30 1
 
< 0.1%
34 1
 
< 0.1%
40 1
 
< 0.1%
ValueCountFrequency (%)
892491 1
< 0.1%
810295 1
< 0.1%
803534 1
< 0.1%
707960 1
< 0.1%
623056 1
< 0.1%
614673 1
< 0.1%
614625 1
< 0.1%
579638 1
< 0.1%
576214 1
< 0.1%
552664 1
< 0.1%

il_util
Real number (ℝ)

High correlation  Missing 

Distinct183
Distinct (%)0.5%
Missing32034
Missing (%)47.2%
Infinite0
Infinite (%)0.0%
Mean69.015173
Minimum0
Maximum321
Zeros199
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:40.680795image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25
Q155
median72
Q385
95-th percentile101
Maximum321
Range321
Interquartile range (IQR)30

Descriptive statistics

Standard deviation23.791554
Coefficient of variation (CV)0.34472932
Kurtosis1.5760246
Mean69.015173
Median Absolute Deviation (MAD)15
Skewness-0.25555373
Sum2469846
Variance566.03802
MonotonicityNot monotonic
2026-01-19T10:07:40.900174image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78 734
 
1.1%
75 708
 
1.0%
72 696
 
1.0%
83 693
 
1.0%
77 693
 
1.0%
70 662
 
1.0%
76 657
 
1.0%
73 649
 
1.0%
88 633
 
0.9%
69 628
 
0.9%
Other values (173) 29034
42.8%
(Missing) 32034
47.2%
ValueCountFrequency (%)
0 199
0.3%
1 19
 
< 0.1%
2 23
 
< 0.1%
3 45
 
0.1%
4 40
 
0.1%
5 32
 
< 0.1%
6 58
 
0.1%
7 39
 
0.1%
8 60
 
0.1%
9 50
 
0.1%
ValueCountFrequency (%)
321 1
< 0.1%
317 1
< 0.1%
291 1
< 0.1%
256 1
< 0.1%
225 1
< 0.1%
218 1
< 0.1%
206 1
< 0.1%
201 1
< 0.1%
199 1
< 0.1%
189 1
< 0.1%

open_rv_12m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct18
Distinct (%)< 0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean1.2958925
Minimum0
Maximum18
Zeros15287
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:40.963414image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum18
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.507265
Coefficient of variation (CV)1.1631096
Kurtosis6.7769523
Mean1.2958925
Median Absolute Deviation (MAD)1
Skewness1.9628963
Sum54202
Variance2.2718478
MonotonicityNot monotonic
2026-01-19T10:07:41.027712image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 15287
22.5%
1 12499
18.4%
2 7146
 
10.5%
3 3619
 
5.3%
4 1649
 
2.4%
5 755
 
1.1%
6 436
 
0.6%
7 215
 
0.3%
8 100
 
0.1%
9 45
 
0.1%
Other values (8) 75
 
0.1%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 15287
22.5%
1 12499
18.4%
2 7146
10.5%
3 3619
 
5.3%
4 1649
 
2.4%
5 755
 
1.1%
6 436
 
0.6%
7 215
 
0.3%
8 100
 
0.1%
9 45
 
0.1%
ValueCountFrequency (%)
18 2
 
< 0.1%
16 2
 
< 0.1%
15 4
 
< 0.1%
14 1
 
< 0.1%
13 7
 
< 0.1%
12 9
 
< 0.1%
11 16
 
< 0.1%
10 34
 
0.1%
9 45
0.1%
8 100
0.1%

open_rv_24m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct30
Distinct (%)0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean2.7593124
Minimum0
Maximum34
Zeros6776
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:41.094998image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile8
Maximum34
Range34
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5995723
Coefficient of variation (CV)0.94210875
Kurtosis6.63081
Mean2.7593124
Median Absolute Deviation (MAD)1
Skewness1.8788817
Sum115411
Variance6.7577764
MonotonicityNot monotonic
2026-01-19T10:07:41.166905image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 8848
 
13.0%
2 7907
 
11.7%
0 6776
 
10.0%
3 6047
 
8.9%
4 4286
 
6.3%
5 2723
 
4.0%
6 1797
 
2.6%
7 1171
 
1.7%
8 789
 
1.2%
9 483
 
0.7%
Other values (20) 999
 
1.5%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 6776
10.0%
1 8848
13.0%
2 7907
11.7%
3 6047
8.9%
4 4286
6.3%
5 2723
 
4.0%
6 1797
 
2.6%
7 1171
 
1.7%
8 789
 
1.2%
9 483
 
0.7%
ValueCountFrequency (%)
34 1
 
< 0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
27 5
< 0.1%
25 2
 
< 0.1%
24 2
 
< 0.1%
23 2
 
< 0.1%
22 2
 
< 0.1%
21 3
 
< 0.1%
20 9
< 0.1%

max_bal_bc
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct14297
Distinct (%)34.2%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean5852.7105
Minimum0
Maximum457521
Zeros1060
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:41.244471image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile348
Q12287
median4426
Q37650
95-th percentile16465.75
Maximum457521
Range457521
Interquartile range (IQR)5363

Descriptive statistics

Standard deviation6325.2785
Coefficient of variation (CV)1.0807434
Kurtosis1007.7865
Mean5852.7105
Median Absolute Deviation (MAD)2479
Skewness17.868095
Sum2.4479547 × 108
Variance40009148
MonotonicityNot monotonic
2026-01-19T10:07:41.327193image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1060
 
1.6%
1900 16
 
< 0.1%
2000 15
 
< 0.1%
6000 15
 
< 0.1%
2931 15
 
< 0.1%
8 15
 
< 0.1%
1972 14
 
< 0.1%
2827 13
 
< 0.1%
3400 13
 
< 0.1%
1500 13
 
< 0.1%
Other values (14287) 40637
59.9%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 1060
1.6%
1 9
 
< 0.1%
2 6
 
< 0.1%
3 3
 
< 0.1%
4 4
 
< 0.1%
5 4
 
< 0.1%
6 4
 
< 0.1%
7 5
 
< 0.1%
8 15
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
457521 1
< 0.1%
361299 1
< 0.1%
298260 1
< 0.1%
211540 1
< 0.1%
150000 1
< 0.1%
112004 1
< 0.1%
91879 1
< 0.1%
75356 1
< 0.1%
64360 1
< 0.1%
55537 1
< 0.1%

all_util
Real number (ℝ)

High correlation  Missing 

Distinct143
Distinct (%)0.3%
Missing26003
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean57.092879
Minimum0
Maximum239
Zeros88
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:41.402347image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21
Q143
median58
Q372
95-th percentile90
Maximum239
Range239
Interquartile range (IQR)29

Descriptive statistics

Standard deviation20.931936
Coefficient of variation (CV)0.36662955
Kurtosis0.06309175
Mean57.092879
Median Absolute Deviation (MAD)14
Skewness-0.11020701
Sum2387510
Variance438.14595
MonotonicityNot monotonic
2026-01-19T10:07:41.476923image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59 838
 
1.2%
57 804
 
1.2%
58 794
 
1.2%
61 789
 
1.2%
62 789
 
1.2%
60 784
 
1.2%
65 761
 
1.1%
63 759
 
1.1%
68 758
 
1.1%
66 757
 
1.1%
Other values (133) 33985
50.1%
(Missing) 26003
38.3%
ValueCountFrequency (%)
0 88
0.1%
1 53
0.1%
2 41
0.1%
3 54
0.1%
4 54
0.1%
5 58
0.1%
6 65
0.1%
7 70
0.1%
8 67
0.1%
9 84
0.1%
ValueCountFrequency (%)
239 1
 
< 0.1%
198 1
 
< 0.1%
173 1
 
< 0.1%
147 1
 
< 0.1%
144 1
 
< 0.1%
139 1
 
< 0.1%
138 1
 
< 0.1%
137 1
 
< 0.1%
135 3
< 0.1%
133 1
 
< 0.1%

total_rev_hi_lim
Real number (ℝ)

High correlation  Missing 

Distinct3587
Distinct (%)5.5%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean34512.001
Minimum0
Maximum1339900
Zeros33
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:41.553419image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6000
Q114600
median25500
Q343100
95-th percentile91600
Maximum1339900
Range1339900
Interquartile range (IQR)28500

Descriptive statistics

Standard deviation34235.669
Coefficient of variation (CV)0.99199314
Kurtosis90.164118
Mean34512.001
Median Absolute Deviation (MAD)12800
Skewness5.515685
Sum2.2684048 × 109
Variance1.172081 × 109
MonotonicityNot monotonic
2026-01-19T10:07:41.640569image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 222
 
0.3%
15500 211
 
0.3%
11000 210
 
0.3%
9000 207
 
0.3%
16500 203
 
0.3%
12000 203
 
0.3%
16000 201
 
0.3%
12500 201
 
0.3%
11500 198
 
0.3%
17000 197
 
0.3%
Other values (3577) 63675
93.9%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 33
< 0.1%
100 1
 
< 0.1%
200 2
 
< 0.1%
300 12
 
< 0.1%
400 4
 
< 0.1%
500 20
< 0.1%
600 7
 
< 0.1%
700 10
 
< 0.1%
800 20
< 0.1%
900 9
 
< 0.1%
ValueCountFrequency (%)
1339900 1
< 0.1%
1116000 1
< 0.1%
1019800 1
< 0.1%
779800 1
< 0.1%
752300 1
< 0.1%
644900 1
< 0.1%
591400 1
< 0.1%
591100 1
< 0.1%
553000 1
< 0.1%
545200 1
< 0.1%

inq_fi
Real number (ℝ)

Missing  Zeros 

Distinct21
Distinct (%)0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean1.0153493
Minimum0
Maximum27
Zeros20858
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:41.711673image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile4
Maximum27
Range27
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4945859
Coefficient of variation (CV)1.4719919
Kurtosis13.565005
Mean1.0153493
Median Absolute Deviation (MAD)1
Skewness2.709908
Sum42468
Variance2.2337871
MonotonicityNot monotonic
2026-01-19T10:07:41.780698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 20858
30.8%
1 10580
15.6%
2 5197
 
7.7%
3 2557
 
3.8%
4 1270
 
1.9%
5 613
 
0.9%
6 303
 
0.4%
7 179
 
0.3%
8 114
 
0.2%
9 61
 
0.1%
Other values (11) 94
 
0.1%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 20858
30.8%
1 10580
15.6%
2 5197
 
7.7%
3 2557
 
3.8%
4 1270
 
1.9%
5 613
 
0.9%
6 303
 
0.4%
7 179
 
0.3%
8 114
 
0.2%
9 61
 
0.1%
ValueCountFrequency (%)
27 1
 
< 0.1%
21 1
 
< 0.1%
19 1
 
< 0.1%
17 1
 
< 0.1%
16 4
 
< 0.1%
15 4
 
< 0.1%
14 8
 
< 0.1%
13 8
 
< 0.1%
12 20
< 0.1%
11 22
< 0.1%

total_cu_tl
Real number (ℝ)

Missing  Zeros 

Distinct37
Distinct (%)0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean1.483001
Minimum0
Maximum39
Zeros22507
Zeros (%)33.2%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:41.850897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum39
Range39
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.6697142
Coefficient of variation (CV)1.8002106
Kurtosis19.224975
Mean1.483001
Median Absolute Deviation (MAD)0
Skewness3.4700985
Sum62028
Variance7.1273739
MonotonicityNot monotonic
2026-01-19T10:07:41.927046image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 22507
33.2%
1 6962
 
10.3%
2 3947
 
5.8%
3 2581
 
3.8%
4 1746
 
2.6%
5 1109
 
1.6%
6 784
 
1.2%
7 595
 
0.9%
8 398
 
0.6%
9 300
 
0.4%
Other values (27) 897
 
1.3%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 22507
33.2%
1 6962
 
10.3%
2 3947
 
5.8%
3 2581
 
3.8%
4 1746
 
2.6%
5 1109
 
1.6%
6 784
 
1.2%
7 595
 
0.9%
8 398
 
0.6%
9 300
 
0.4%
ValueCountFrequency (%)
39 1
 
< 0.1%
38 1
 
< 0.1%
37 2
< 0.1%
36 1
 
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
30 3
< 0.1%
29 1
 
< 0.1%
28 4
< 0.1%
27 2
< 0.1%

inq_last_12m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct30
Distinct (%)0.1%
Missing25995
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean2.0482475
Minimum0
Maximum41
Zeros11943
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:42.000698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile7
Maximum41
Range41
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4009394
Coefficient of variation (CV)1.172192
Kurtosis12.448494
Mean2.0482475
Median Absolute Deviation (MAD)1
Skewness2.4788421
Sum85670
Variance5.7645101
MonotonicityNot monotonic
2026-01-19T10:07:42.064482image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 11943
17.6%
1 10150
 
15.0%
2 7121
 
10.5%
3 4598
 
6.8%
4 2824
 
4.2%
5 1897
 
2.8%
6 1114
 
1.6%
7 747
 
1.1%
8 475
 
0.7%
9 292
 
0.4%
Other values (20) 665
 
1.0%
(Missing) 25995
38.3%
ValueCountFrequency (%)
0 11943
17.6%
1 10150
15.0%
2 7121
10.5%
3 4598
 
6.8%
4 2824
 
4.2%
5 1897
 
2.8%
6 1114
 
1.6%
7 747
 
1.1%
8 475
 
0.7%
9 292
 
0.4%
ValueCountFrequency (%)
41 1
 
< 0.1%
39 1
 
< 0.1%
32 2
 
< 0.1%
29 2
 
< 0.1%
27 2
 
< 0.1%
24 3
 
< 0.1%
23 2
 
< 0.1%
22 1
 
< 0.1%
21 3
 
< 0.1%
20 11
< 0.1%

acc_open_past_24mths
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct32
Distinct (%)< 0.1%
Missing1485
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean4.5293204
Minimum0
Maximum34
Zeros3038
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:42.133258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q36
95-th percentile10
Maximum34
Range34
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.153697
Coefficient of variation (CV)0.69628481
Kurtosis3.1448413
Mean4.5293204
Median Absolute Deviation (MAD)2
Skewness1.2964384
Sum300457
Variance9.945805
MonotonicityNot monotonic
2026-01-19T10:07:42.207179image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
3 9754
14.4%
4 9269
13.7%
2 9001
13.3%
5 7840
11.6%
1 6781
10.0%
6 6093
9.0%
7 4471
6.6%
8 3194
 
4.7%
0 3038
 
4.5%
9 2240
 
3.3%
Other values (22) 4655
6.9%
ValueCountFrequency (%)
0 3038
 
4.5%
1 6781
10.0%
2 9001
13.3%
3 9754
14.4%
4 9269
13.7%
5 7840
11.6%
6 6093
9.0%
7 4471
6.6%
8 3194
 
4.7%
9 2240
 
3.3%
ValueCountFrequency (%)
34 1
 
< 0.1%
31 2
 
< 0.1%
29 2
 
< 0.1%
28 1
 
< 0.1%
27 6
 
< 0.1%
26 1
 
< 0.1%
25 7
 
< 0.1%
24 10
< 0.1%
23 13
< 0.1%
22 21
< 0.1%

avg_cur_bal
Real number (ℝ)

High correlation  Missing 

Distinct28640
Distinct (%)43.6%
Missing2096
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean13623.92
Minimum0
Maximum445856
Zeros29
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:42.283873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1085
Q13103
median7378
Q318791
95-th percentile43809.6
Maximum445856
Range445856
Interquartile range (IQR)15688

Descriptive statistics

Standard deviation16700.78
Coefficient of variation (CV)1.2258425
Kurtosis37.20439
Mean13623.92
Median Absolute Deviation (MAD)5398
Skewness3.9099712
Sum8.9543214 × 108
Variance2.7891607 × 108
MonotonicityNot monotonic
2026-01-19T10:07:42.360308image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
 
< 0.1%
1626 18
 
< 0.1%
3457 16
 
< 0.1%
1629 15
 
< 0.1%
2296 15
 
< 0.1%
1080 15
 
< 0.1%
1557 14
 
< 0.1%
2633 14
 
< 0.1%
2040 14
 
< 0.1%
2591 14
 
< 0.1%
Other values (28630) 65561
96.7%
(Missing) 2096
 
3.1%
ValueCountFrequency (%)
0 29
< 0.1%
1 2
 
< 0.1%
2 5
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
445856 1
< 0.1%
383983 1
< 0.1%
362147 1
< 0.1%
355013 1
< 0.1%
310429 1
< 0.1%
290204 1
< 0.1%
285326 1
< 0.1%
274635 1
< 0.1%
241662 1
< 0.1%
233099 1
< 0.1%

bc_open_to_buy
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct25526
Distinct (%)38.9%
Missing2202
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean11374.105
Minimum0
Maximum469679
Zeros979
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:42.431949image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile155
Q11711
median5449
Q314109
95-th percentile42879.2
Maximum469679
Range469679
Interquartile range (IQR)12398

Descriptive statistics

Standard deviation16739.875
Coefficient of variation (CV)1.4717531
Kurtosis32.64609
Mean11374.105
Median Absolute Deviation (MAD)4563
Skewness3.9787846
Sum7.463574 × 108
Variance2.8022341 × 108
MonotonicityNot monotonic
2026-01-19T10:07:42.507689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 979
 
1.4%
2000 60
 
0.1%
3000 53
 
0.1%
500 50
 
0.1%
2500 49
 
0.1%
5000 48
 
0.1%
1000 47
 
0.1%
1500 39
 
0.1%
300 38
 
0.1%
4000 37
 
0.1%
Other values (25516) 64219
94.7%
(Missing) 2202
 
3.2%
ValueCountFrequency (%)
0 979
1.4%
1 7
 
< 0.1%
2 13
 
< 0.1%
3 9
 
< 0.1%
4 12
 
< 0.1%
5 15
 
< 0.1%
6 18
 
< 0.1%
7 12
 
< 0.1%
8 14
 
< 0.1%
9 10
 
< 0.1%
ValueCountFrequency (%)
469679 1
< 0.1%
371701 1
< 0.1%
295713 1
< 0.1%
247574 1
< 0.1%
246153 1
< 0.1%
245519 1
< 0.1%
241778 1
< 0.1%
224364 1
< 0.1%
221273 1
< 0.1%
217362 1
< 0.1%

bc_util
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct1125
Distinct (%)1.7%
Missing2235
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean57.918065
Minimum0
Maximum201.9
Zeros849
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:42.583637image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.8
Q135.4
median60.35
Q383.3
95-th percentile97.8
Maximum201.9
Range201.9
Interquartile range (IQR)47.9

Descriptive statistics

Standard deviation28.610787
Coefficient of variation (CV)0.49398728
Kurtosis-1.0125135
Mean57.918065
Median Absolute Deviation (MAD)23.75
Skewness-0.26924216
Sum3798614.2
Variance818.57715
MonotonicityNot monotonic
2026-01-19T10:07:42.666647image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 849
 
1.3%
96 196
 
0.3%
98 191
 
0.3%
97 170
 
0.3%
94 160
 
0.2%
93 159
 
0.2%
95 156
 
0.2%
99 145
 
0.2%
92 138
 
0.2%
88 127
 
0.2%
Other values (1115) 63295
93.3%
(Missing) 2235
 
3.3%
ValueCountFrequency (%)
0 849
1.3%
0.1 62
 
0.1%
0.2 62
 
0.1%
0.3 43
 
0.1%
0.4 34
 
0.1%
0.5 39
 
0.1%
0.6 33
 
< 0.1%
0.7 45
 
0.1%
0.8 36
 
0.1%
0.9 34
 
0.1%
ValueCountFrequency (%)
201.9 1
< 0.1%
161 1
< 0.1%
140.7 1
< 0.1%
137.9 1
< 0.1%
134.5 1
< 0.1%
132.2 1
< 0.1%
131.7 1
< 0.1%
130.5 1
< 0.1%
129.6 1
< 0.1%
129.5 1
< 0.1%

chargeoff_within_12_mths
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.0087296321
Minimum0
Maximum7
Zeros67290
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:42.731451image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.10716729
Coefficient of variation (CV)12.276266
Kurtosis512.30711
Mean0.0087296321
Median Absolute Deviation (MAD)0
Skewness17.415629
Sum592
Variance0.011484827
MonotonicityNot monotonic
2026-01-19T10:07:42.794038image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 67290
99.2%
1 475
 
0.7%
2 39
 
0.1%
3 8
 
< 0.1%
4 2
 
< 0.1%
7 1
 
< 0.1%
(Missing) 6
 
< 0.1%
ValueCountFrequency (%)
0 67290
99.2%
1 475
 
0.7%
2 39
 
0.1%
3 8
 
< 0.1%
4 2
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
4 2
 
< 0.1%
3 8
 
< 0.1%
2 39
 
0.1%
1 475
 
0.7%
0 67290
99.2%

delinq_amnt
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct164
Distinct (%)0.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean9.8336037
Minimum0
Maximum65000
Zeros67629
Zeros (%)99.7%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:42.866859image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum65000
Range65000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation593.07904
Coefficient of variation (CV)60.311465
Kurtosis8151.2598
Mean9.8336037
Median Absolute Deviation (MAD)0
Skewness85.714751
Sum666915
Variance351742.75
MonotonicityNot monotonic
2026-01-19T10:07:42.944914image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67629
99.7%
30 5
 
< 0.1%
25 4
 
< 0.1%
55 4
 
< 0.1%
136 2
 
< 0.1%
81 2
 
< 0.1%
84 2
 
< 0.1%
274 2
 
< 0.1%
69 2
 
< 0.1%
65000 2
 
< 0.1%
Other values (154) 166
 
0.2%
ValueCountFrequency (%)
0 67629
99.7%
3 1
 
< 0.1%
8 1
 
< 0.1%
11 1
 
< 0.1%
13 1
 
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
17 1
 
< 0.1%
20 1
 
< 0.1%
22 1
 
< 0.1%
ValueCountFrequency (%)
65000 2
< 0.1%
62302 1
< 0.1%
52201 1
< 0.1%
47641 1
< 0.1%
38665 1
< 0.1%
30114 1
< 0.1%
29046 1
< 0.1%
27921 1
< 0.1%
22765 1
< 0.1%
20494 1
< 0.1%

mo_sin_old_il_acct
Real number (ℝ)

Missing 

Distinct423
Distinct (%)0.7%
Missing4131
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean126.25351
Minimum1
Maximum553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:43.019720image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32
Q197
median130
Q3154
95-th percentile214
Maximum553
Range552
Interquartile range (IQR)57

Descriptive statistics

Standard deviation53.320312
Coefficient of variation (CV)0.42232736
Kurtosis2.0370599
Mean126.25351
Median Absolute Deviation (MAD)27
Skewness0.40217318
Sum8041086
Variance2843.0556
MonotonicityNot monotonic
2026-01-19T10:07:43.091421image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
130 778
 
1.1%
135 760
 
1.1%
139 759
 
1.1%
128 756
 
1.1%
121 755
 
1.1%
132 750
 
1.1%
131 745
 
1.1%
134 743
 
1.1%
127 743
 
1.1%
133 740
 
1.1%
Other values (413) 56161
82.8%
(Missing) 4131
 
6.1%
ValueCountFrequency (%)
1 14
 
< 0.1%
2 25
 
< 0.1%
3 43
0.1%
4 55
0.1%
5 57
0.1%
6 58
0.1%
7 67
0.1%
8 84
0.1%
9 97
0.1%
10 81
0.1%
ValueCountFrequency (%)
553 1
< 0.1%
547 1
< 0.1%
540 1
< 0.1%
537 1
< 0.1%
534 2
< 0.1%
516 1
< 0.1%
501 1
< 0.1%
469 1
< 0.1%
466 2
< 0.1%
455 1
< 0.1%

mo_sin_old_rev_tl_op
Real number (ℝ)

Missing 

Distinct639
Distinct (%)1.0%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean181.52501
Minimum3
Maximum766
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:43.282970image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile49
Q1116
median164
Q3231
95-th percentile368
Maximum766
Range763
Interquartile range (IQR)115

Descriptive statistics

Standard deviation97.221198
Coefficient of variation (CV)0.53558018
Kurtosis1.4414163
Mean181.52501
Median Absolute Deviation (MAD)56
Skewness1.0226811
Sum11931276
Variance9451.9614
MonotonicityNot monotonic
2026-01-19T10:07:43.365343image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
136 398
 
0.6%
132 388
 
0.6%
137 384
 
0.6%
131 382
 
0.6%
142 374
 
0.6%
129 372
 
0.5%
133 368
 
0.5%
119 367
 
0.5%
145 365
 
0.5%
127 364
 
0.5%
Other values (629) 61966
91.4%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 1
 
< 0.1%
7 4
 
< 0.1%
8 4
 
< 0.1%
9 5
 
< 0.1%
10 3
 
< 0.1%
11 3
 
< 0.1%
12 12
< 0.1%
13 13
< 0.1%
14 21
< 0.1%
ValueCountFrequency (%)
766 1
< 0.1%
727 1
< 0.1%
718 1
< 0.1%
715 1
< 0.1%
708 2
< 0.1%
701 1
< 0.1%
700 1
< 0.1%
670 1
< 0.1%
669 1
< 0.1%
666 1
< 0.1%

mo_sin_rcnt_rev_tl_op
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct191
Distinct (%)0.3%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean14.00779
Minimum0
Maximum313
Zeros966
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:43.444887image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median8
Q317
95-th percentile46
Maximum313
Range313
Interquartile range (IQR)13

Descriptive statistics

Standard deviation17.518899
Coefficient of variation (CV)1.2506541
Kurtosis21.355627
Mean14.00779
Median Absolute Deviation (MAD)5
Skewness3.5843627
Sum920704
Variance306.91183
MonotonicityNot monotonic
2026-01-19T10:07:43.521027image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 4951
 
7.3%
3 4929
 
7.3%
4 4443
 
6.6%
1 4147
 
6.1%
5 3982
 
5.9%
6 3567
 
5.3%
7 3208
 
4.7%
8 2995
 
4.4%
9 2603
 
3.8%
10 2397
 
3.5%
Other values (181) 28506
42.0%
ValueCountFrequency (%)
0 966
 
1.4%
1 4147
6.1%
2 4951
7.3%
3 4929
7.3%
4 4443
6.6%
5 3982
5.9%
6 3567
5.3%
7 3208
4.7%
8 2995
4.4%
9 2603
3.8%
ValueCountFrequency (%)
313 1
< 0.1%
300 1
< 0.1%
273 1
< 0.1%
272 1
< 0.1%
258 1
< 0.1%
252 1
< 0.1%
249 1
< 0.1%
247 1
< 0.1%
240 1
< 0.1%
223 1
< 0.1%

mo_sin_rcnt_tl
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct135
Distinct (%)0.2%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean8.2880355
Minimum0
Maximum200
Zeros1003
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:43.600606image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median6
Q310
95-th percentile24
Maximum200
Range200
Interquartile range (IQR)7

Descriptive statistics

Standard deviation9.2267861
Coefficient of variation (CV)1.1132657
Kurtosis38.520088
Mean8.2880355
Median Absolute Deviation (MAD)3
Skewness4.4556185
Sum544756
Variance85.133581
MonotonicityNot monotonic
2026-01-19T10:07:43.682697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 6994
10.3%
2 6993
10.3%
4 6122
 
9.0%
1 5487
 
8.1%
5 5247
 
7.7%
6 4523
 
6.7%
7 4029
 
5.9%
8 3501
 
5.2%
9 2959
 
4.4%
10 2449
 
3.6%
Other values (125) 17424
25.7%
ValueCountFrequency (%)
0 1003
 
1.5%
1 5487
8.1%
2 6993
10.3%
3 6994
10.3%
4 6122
9.0%
5 5247
7.7%
6 4523
6.7%
7 4029
5.9%
8 3501
5.2%
9 2959
4.4%
ValueCountFrequency (%)
200 1
< 0.1%
189 1
< 0.1%
181 1
< 0.1%
170 1
< 0.1%
166 1
< 0.1%
151 1
< 0.1%
150 1
< 0.1%
147 2
< 0.1%
136 1
< 0.1%
135 1
< 0.1%

mort_acc
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct23
Distinct (%)< 0.1%
Missing1485
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean1.5512391
Minimum0
Maximum45
Zeros27882
Zeros (%)41.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:43.755299image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum45
Range45
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9016278
Coefficient of variation (CV)1.2258766
Kurtosis8.0794448
Mean1.5512391
Median Absolute Deviation (MAD)1
Skewness1.7812495
Sum102903
Variance3.6161881
MonotonicityNot monotonic
2026-01-19T10:07:43.817371image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 27882
41.1%
1 11775
17.4%
2 9982
 
14.7%
3 6883
 
10.1%
4 4426
 
6.5%
5 2606
 
3.8%
6 1382
 
2.0%
7 670
 
1.0%
8 349
 
0.5%
9 167
 
0.2%
Other values (13) 214
 
0.3%
(Missing) 1485
 
2.2%
ValueCountFrequency (%)
0 27882
41.1%
1 11775
17.4%
2 9982
 
14.7%
3 6883
 
10.1%
4 4426
 
6.5%
5 2606
 
3.8%
6 1382
 
2.0%
7 670
 
1.0%
8 349
 
0.5%
9 167
 
0.2%
ValueCountFrequency (%)
45 1
 
< 0.1%
24 1
 
< 0.1%
23 1
 
< 0.1%
21 2
 
< 0.1%
20 1
 
< 0.1%
18 2
 
< 0.1%
16 4
 
< 0.1%
15 2
 
< 0.1%
14 8
 
< 0.1%
13 24
< 0.1%

mths_since_recent_bc
Real number (ℝ)

High correlation  Missing 

Distinct326
Distinct (%)0.5%
Missing2164
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean24.792589
Minimum0
Maximum584
Zeros363
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:43.884951image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q16
median14
Q330
95-th percentile88
Maximum584
Range584
Interquartile range (IQR)24

Descriptive statistics

Standard deviation32.32171
Coefficient of variation (CV)1.3036843
Kurtosis21.467395
Mean24.792589
Median Absolute Deviation (MAD)9
Skewness3.5515867
Sum1627807
Variance1044.6929
MonotonicityNot monotonic
2026-01-19T10:07:43.960510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 3221
 
4.7%
2 3075
 
4.5%
4 3048
 
4.5%
5 2863
 
4.2%
6 2653
 
3.9%
7 2518
 
3.7%
8 2389
 
3.5%
9 2208
 
3.3%
10 2142
 
3.2%
1 2060
 
3.0%
Other values (316) 39480
58.2%
(Missing) 2164
 
3.2%
ValueCountFrequency (%)
0 363
 
0.5%
1 2060
3.0%
2 3075
4.5%
3 3221
4.7%
4 3048
4.5%
5 2863
4.2%
6 2653
3.9%
7 2518
3.7%
8 2389
3.5%
9 2208
3.3%
ValueCountFrequency (%)
584 1
< 0.1%
577 1
< 0.1%
564 1
< 0.1%
489 1
< 0.1%
464 1
< 0.1%
436 1
< 0.1%
422 1
< 0.1%
420 1
< 0.1%
395 1
< 0.1%
387 1
< 0.1%

mths_since_recent_bc_dlq
Real number (ℝ)

High correlation  Missing 

Distinct126
Distinct (%)0.8%
Missing52121
Missing (%)76.9%
Infinite0
Infinite (%)0.0%
Mean39.467452
Minimum0
Maximum155
Zeros22
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:44.039126image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q121
median38
Q357
95-th percentile77
Maximum155
Range155
Interquartile range (IQR)36

Descriptive statistics

Standard deviation22.722055
Coefficient of variation (CV)0.57571627
Kurtosis-0.68062618
Mean39.467452
Median Absolute Deviation (MAD)18
Skewness0.32828949
Sum619639
Variance516.29176
MonotonicityNot monotonic
2026-01-19T10:07:44.121863image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 268
 
0.4%
25 260
 
0.4%
45 256
 
0.4%
42 256
 
0.4%
27 255
 
0.4%
30 255
 
0.4%
41 254
 
0.4%
46 253
 
0.4%
13 251
 
0.4%
19 250
 
0.4%
Other values (116) 13142
 
19.4%
(Missing) 52121
76.9%
ValueCountFrequency (%)
0 22
 
< 0.1%
1 82
 
0.1%
2 81
 
0.1%
3 137
0.2%
4 154
0.2%
5 177
0.3%
6 173
0.3%
7 175
0.3%
8 176
0.3%
9 221
0.3%
ValueCountFrequency (%)
155 1
 
< 0.1%
146 1
 
< 0.1%
140 1
 
< 0.1%
126 1
 
< 0.1%
125 1
 
< 0.1%
124 1
 
< 0.1%
120 2
< 0.1%
119 2
< 0.1%
118 3
< 0.1%
116 1
 
< 0.1%

mths_since_recent_inq
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct26
Distinct (%)< 0.1%
Missing8909
Missing (%)13.1%
Infinite0
Infinite (%)0.0%
Mean6.9929386
Minimum0
Maximum25
Zeros5055
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:44.198519image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q311
95-th percentile19
Maximum25
Range25
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.9484027
Coefficient of variation (CV)0.8506299
Kurtosis-0.029010055
Mean6.9929386
Median Absolute Deviation (MAD)4
Skewness0.89121749
Sum411968
Variance35.383495
MonotonicityNot monotonic
2026-01-19T10:07:44.269652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 6518
 
9.6%
2 5219
 
7.7%
0 5055
 
7.5%
3 4733
 
7.0%
4 4189
 
6.2%
5 3914
 
5.8%
6 3487
 
5.1%
7 3180
 
4.7%
8 2859
 
4.2%
9 2560
 
3.8%
Other values (16) 17198
25.4%
(Missing) 8909
13.1%
ValueCountFrequency (%)
0 5055
7.5%
1 6518
9.6%
2 5219
7.7%
3 4733
7.0%
4 4189
6.2%
5 3914
5.8%
6 3487
5.1%
7 3180
4.7%
8 2859
4.2%
9 2560
 
3.8%
ValueCountFrequency (%)
25 2
 
< 0.1%
24 259
 
0.4%
23 571
0.8%
22 605
0.9%
21 640
0.9%
20 657
1.0%
19 806
1.2%
18 902
1.3%
17 950
1.4%
16 1155
1.7%

mths_since_recent_revol_delinq
Real number (ℝ)

High correlation  Missing 

Distinct124
Distinct (%)0.6%
Missing45580
Missing (%)67.2%
Infinite0
Infinite (%)0.0%
Mean35.942044
Minimum0
Maximum155
Zeros33
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:44.346763image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q117
median33
Q352
95-th percentile76
Maximum155
Range155
Interquartile range (IQR)35

Descriptive statistics

Standard deviation22.409099
Coefficient of variation (CV)0.62347871
Kurtosis-0.61013205
Mean35.942044
Median Absolute Deviation (MAD)17
Skewness0.46718347
Sum799387
Variance502.16773
MonotonicityNot monotonic
2026-01-19T10:07:44.434079image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 406
 
0.6%
13 402
 
0.6%
11 387
 
0.6%
15 386
 
0.6%
9 382
 
0.6%
22 378
 
0.6%
19 373
 
0.5%
20 373
 
0.5%
24 373
 
0.5%
18 372
 
0.5%
Other values (114) 18409
27.1%
(Missing) 45580
67.2%
ValueCountFrequency (%)
0 33
 
< 0.1%
1 145
 
0.2%
2 179
0.3%
3 239
0.4%
4 281
0.4%
5 304
0.4%
6 357
0.5%
7 363
0.5%
8 360
0.5%
9 382
0.6%
ValueCountFrequency (%)
155 1
< 0.1%
146 1
< 0.1%
129 1
< 0.1%
126 1
< 0.1%
125 2
< 0.1%
124 2
< 0.1%
120 1
< 0.1%
118 2
< 0.1%
116 1
< 0.1%
115 1
< 0.1%

num_accts_ever_120_pd
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct23
Distinct (%)< 0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.49726144
Minimum0
Maximum29
Zeros50631
Zeros (%)74.7%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:44.505293image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum29
Range29
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3137194
Coefficient of variation (CV)2.6419088
Kurtosis36.316028
Mean0.49726144
Median Absolute Deviation (MAD)0
Skewness4.8281247
Sum32684
Variance1.7258586
MonotonicityNot monotonic
2026-01-19T10:07:44.572873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 50631
74.7%
1 8074
 
11.9%
2 3239
 
4.8%
3 1408
 
2.1%
4 850
 
1.3%
5 566
 
0.8%
6 330
 
0.5%
7 229
 
0.3%
8 139
 
0.2%
9 83
 
0.1%
Other values (13) 179
 
0.3%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 50631
74.7%
1 8074
 
11.9%
2 3239
 
4.8%
3 1408
 
2.1%
4 850
 
1.3%
5 566
 
0.8%
6 330
 
0.5%
7 229
 
0.3%
8 139
 
0.2%
9 83
 
0.1%
ValueCountFrequency (%)
29 1
 
< 0.1%
24 2
 
< 0.1%
20 2
 
< 0.1%
19 2
 
< 0.1%
18 5
 
< 0.1%
17 4
 
< 0.1%
16 11
< 0.1%
15 5
 
< 0.1%
14 16
< 0.1%
13 16
< 0.1%

num_actv_bc_tl
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct26
Distinct (%)< 0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean3.6658197
Minimum0
Maximum35
Zeros1485
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:44.640046image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile8
Maximum35
Range35
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.321887
Coefficient of variation (CV)0.63338822
Kurtosis4.2729469
Mean3.6658197
Median Absolute Deviation (MAD)1
Skewness1.4511281
Sum240947
Variance5.3911594
MonotonicityNot monotonic
2026-01-19T10:07:44.709678image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
3 13677
20.2%
2 13324
19.6%
4 10655
15.7%
1 7892
11.6%
5 7206
10.6%
6 4541
 
6.7%
7 2752
 
4.1%
8 1644
 
2.4%
0 1485
 
2.2%
9 1020
 
1.5%
Other values (16) 1532
 
2.3%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 1485
 
2.2%
1 7892
11.6%
2 13324
19.6%
3 13677
20.2%
4 10655
15.7%
5 7206
10.6%
6 4541
 
6.7%
7 2752
 
4.1%
8 1644
 
2.4%
9 1020
 
1.5%
ValueCountFrequency (%)
35 1
 
< 0.1%
24 1
 
< 0.1%
23 4
 
< 0.1%
22 2
 
< 0.1%
21 2
 
< 0.1%
20 7
 
< 0.1%
19 8
 
< 0.1%
18 14
< 0.1%
17 32
< 0.1%
16 33
< 0.1%

num_actv_rev_tl
Real number (ℝ)

High correlation  Missing 

Distinct41
Distinct (%)0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean5.6300815
Minimum0
Maximum48
Zeros322
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:44.783773image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median5
Q37
95-th percentile12
Maximum48
Range48
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.403765
Coefficient of variation (CV)0.60456762
Kurtosis5.2131365
Mean5.6300815
Median Absolute Deviation (MAD)2
Skewness1.6009335
Sum370054
Variance11.585616
MonotonicityNot monotonic
2026-01-19T10:07:44.863352image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
4 10049
14.8%
3 9272
13.7%
5 8996
13.3%
6 7423
10.9%
2 6503
9.6%
7 5730
8.4%
8 4165
6.1%
9 3079
 
4.5%
1 2579
 
3.8%
10 2140
 
3.2%
Other values (31) 5792
8.5%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 322
 
0.5%
1 2579
 
3.8%
2 6503
9.6%
3 9272
13.7%
4 10049
14.8%
5 8996
13.3%
6 7423
10.9%
7 5730
8.4%
8 4165
6.1%
9 3079
 
4.5%
ValueCountFrequency (%)
48 1
 
< 0.1%
41 1
 
< 0.1%
40 3
< 0.1%
38 1
 
< 0.1%
37 2
< 0.1%
35 2
< 0.1%
34 2
< 0.1%
33 1
 
< 0.1%
32 2
< 0.1%
31 3
< 0.1%

num_bc_sats
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct39
Distinct (%)0.1%
Missing1740
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean4.7624279
Minimum0
Maximum54
Zeros691
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:44.940774image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q36
95-th percentile10
Maximum54
Range54
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.032944
Coefficient of variation (CV)0.63684827
Kurtosis6.8722121
Mean4.7624279
Median Absolute Deviation (MAD)2
Skewness1.7419825
Sum314706
Variance9.1987493
MonotonicityNot monotonic
2026-01-19T10:07:45.010499image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
3 11292
16.6%
4 10875
16.0%
2 9152
13.5%
5 8687
12.8%
6 6355
9.4%
1 4639
6.8%
7 4574
6.7%
8 3056
 
4.5%
9 2145
 
3.2%
10 1456
 
2.1%
Other values (29) 3850
 
5.7%
(Missing) 1740
 
2.6%
ValueCountFrequency (%)
0 691
 
1.0%
1 4639
6.8%
2 9152
13.5%
3 11292
16.6%
4 10875
16.0%
5 8687
12.8%
6 6355
9.4%
7 4574
6.7%
8 3056
 
4.5%
9 2145
 
3.2%
ValueCountFrequency (%)
54 1
 
< 0.1%
47 1
 
< 0.1%
37 1
 
< 0.1%
36 1
 
< 0.1%
35 1
 
< 0.1%
34 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 2
< 0.1%
29 4
< 0.1%

num_bc_tl
Real number (ℝ)

High correlation  Missing 

Distinct49
Distinct (%)0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean7.7496805
Minimum0
Maximum64
Zeros185
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:45.084098image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q14
median7
Q310
95-th percentile17
Maximum64
Range64
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.7444187
Coefficient of variation (CV)0.6122083
Kurtosis4.1383721
Mean7.7496805
Median Absolute Deviation (MAD)3
Skewness1.44387
Sum509371
Variance22.509509
MonotonicityNot monotonic
2026-01-19T10:07:45.162024image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
5 6949
10.2%
4 6757
10.0%
6 6554
9.7%
7 6008
8.9%
3 5440
8.0%
8 5424
8.0%
9 4643
 
6.8%
10 3689
 
5.4%
2 3660
 
5.4%
11 3145
 
4.6%
Other values (39) 13459
19.8%
ValueCountFrequency (%)
0 185
 
0.3%
1 1458
 
2.1%
2 3660
5.4%
3 5440
8.0%
4 6757
10.0%
5 6949
10.2%
6 6554
9.7%
7 6008
8.9%
8 5424
8.0%
9 4643
6.8%
ValueCountFrequency (%)
64 1
 
< 0.1%
58 3
< 0.1%
57 1
 
< 0.1%
54 1
 
< 0.1%
52 1
 
< 0.1%
46 1
 
< 0.1%
45 2
< 0.1%
43 1
 
< 0.1%
40 2
< 0.1%
39 4
< 0.1%

num_il_tl
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct79
Distinct (%)0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean8.4442399
Minimum0
Maximum127
Zeros2041
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:45.238422image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median6
Q311
95-th percentile23
Maximum127
Range127
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.4093152
Coefficient of variation (CV)0.87744016
Kurtosis8.2949562
Mean8.4442399
Median Absolute Deviation (MAD)3
Skewness2.1407905
Sum555023
Variance54.897951
MonotonicityNot monotonic
2026-01-19T10:07:45.322518image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 5730
 
8.4%
3 5713
 
8.4%
5 5459
 
8.0%
2 5156
 
7.6%
6 4962
 
7.3%
7 4425
 
6.5%
1 3946
 
5.8%
8 3932
 
5.8%
9 3378
 
5.0%
10 2886
 
4.3%
Other values (69) 20141
29.7%
ValueCountFrequency (%)
0 2041
 
3.0%
1 3946
5.8%
2 5156
7.6%
3 5713
8.4%
4 5730
8.4%
5 5459
8.0%
6 4962
7.3%
7 4425
6.5%
8 3932
5.8%
9 3378
5.0%
ValueCountFrequency (%)
127 1
< 0.1%
101 1
< 0.1%
94 1
< 0.1%
86 2
< 0.1%
81 2
< 0.1%
77 1
< 0.1%
74 2
< 0.1%
73 1
< 0.1%
72 1
< 0.1%
71 2
< 0.1%

num_op_rev_tl
Real number (ℝ)

High correlation  Missing 

Distinct50
Distinct (%)0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean8.236718
Minimum0
Maximum63
Zeros28
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:45.519273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q15
median7
Q310
95-th percentile17
Maximum63
Range63
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.6935318
Coefficient of variation (CV)0.56983034
Kurtosis4.5342258
Mean8.236718
Median Absolute Deviation (MAD)3
Skewness1.522419
Sum541383
Variance22.029241
MonotonicityNot monotonic
2026-01-19T10:07:45.595290image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 7056
10.4%
5 6892
10.2%
7 6664
9.8%
4 6252
9.2%
8 5877
8.7%
9 4988
 
7.4%
3 4377
 
6.5%
10 4267
 
6.3%
11 3480
 
5.1%
12 2775
 
4.1%
Other values (40) 13100
19.3%
ValueCountFrequency (%)
0 28
 
< 0.1%
1 555
 
0.8%
2 2383
 
3.5%
3 4377
6.5%
4 6252
9.2%
5 6892
10.2%
6 7056
10.4%
7 6664
9.8%
8 5877
8.7%
9 4988
7.4%
ValueCountFrequency (%)
63 1
 
< 0.1%
58 1
 
< 0.1%
56 1
 
< 0.1%
49 1
 
< 0.1%
48 4
< 0.1%
47 3
< 0.1%
44 1
 
< 0.1%
43 2
 
< 0.1%
41 4
< 0.1%
40 6
< 0.1%

num_rev_accts
Real number (ℝ)

High correlation  Missing 

Distinct79
Distinct (%)0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean14.041124
Minimum2
Maximum128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:45.675861image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q18
median12
Q318
95-th percentile29
Maximum128
Range126
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.1158782
Coefficient of variation (CV)0.57800773
Kurtosis4.3868533
Mean14.041124
Median Absolute Deviation (MAD)5
Skewness1.43968
Sum922895
Variance65.86748
MonotonicityNot monotonic
2026-01-19T10:07:45.759117image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 4012
 
5.9%
10 3889
 
5.7%
11 3794
 
5.6%
8 3750
 
5.5%
7 3722
 
5.5%
12 3688
 
5.4%
13 3569
 
5.3%
6 3339
 
4.9%
14 3215
 
4.7%
15 2973
 
4.4%
Other values (69) 29777
43.9%
ValueCountFrequency (%)
2 665
 
1.0%
3 1272
 
1.9%
4 2169
3.2%
5 2720
4.0%
6 3339
4.9%
7 3722
5.5%
8 3750
5.5%
9 4012
5.9%
10 3889
5.7%
11 3794
5.6%
ValueCountFrequency (%)
128 1
< 0.1%
119 1
< 0.1%
107 1
< 0.1%
90 1
< 0.1%
87 1
< 0.1%
84 1
< 0.1%
81 2
< 0.1%
79 1
< 0.1%
76 1
< 0.1%
72 1
< 0.1%

num_rev_tl_bal_gt_0
Real number (ℝ)

High correlation  Missing 

Distinct37
Distinct (%)0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean5.5792813
Minimum0
Maximum40
Zeros313
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:45.836752image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median5
Q37
95-th percentile12
Maximum40
Range40
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3094559
Coefficient of variation (CV)0.59316886
Kurtosis3.9966473
Mean5.5792813
Median Absolute Deviation (MAD)2
Skewness1.4686817
Sum366715
Variance10.952498
MonotonicityNot monotonic
2026-01-19T10:07:45.912925image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
4 10102
14.9%
3 9377
13.8%
5 9032
13.3%
6 7479
11.0%
2 6503
9.6%
7 5820
8.6%
8 4117
6.1%
9 3100
 
4.6%
1 2575
 
3.8%
10 2118
 
3.1%
Other values (27) 5505
8.1%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 313
 
0.5%
1 2575
 
3.8%
2 6503
9.6%
3 9377
13.8%
4 10102
14.9%
5 9032
13.3%
6 7479
11.0%
7 5820
8.6%
8 4117
6.1%
9 3100
 
4.6%
ValueCountFrequency (%)
40 1
 
< 0.1%
38 1
 
< 0.1%
34 1
 
< 0.1%
33 1
 
< 0.1%
32 2
 
< 0.1%
31 2
 
< 0.1%
30 4
 
< 0.1%
29 2
 
< 0.1%
28 4
 
< 0.1%
27 12
< 0.1%

num_sats
Real number (ℝ)

High correlation  Missing 

Distinct59
Distinct (%)0.1%
Missing1740
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean11.624446
Minimum0
Maximum94
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:45.992126image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q18
median11
Q314
95-th percentile22
Maximum94
Range94
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.6454637
Coefficient of variation (CV)0.48565444
Kurtosis3.6865072
Mean11.624446
Median Absolute Deviation (MAD)3
Skewness1.3250213
Sum768155
Variance31.87126
MonotonicityNot monotonic
2026-01-19T10:07:46.071756image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 5691
 
8.4%
8 5587
 
8.2%
10 5485
 
8.1%
11 5117
 
7.5%
7 5095
 
7.5%
12 4521
 
6.7%
6 4308
 
6.4%
13 4034
 
5.9%
14 3476
 
5.1%
5 3096
 
4.6%
Other values (49) 19671
29.0%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 57
 
0.1%
2 304
 
0.4%
3 903
 
1.3%
4 1996
 
2.9%
5 3096
4.6%
6 4308
6.4%
7 5095
7.5%
8 5587
8.2%
9 5691
8.4%
ValueCountFrequency (%)
94 1
 
< 0.1%
66 1
 
< 0.1%
61 1
 
< 0.1%
60 1
 
< 0.1%
56 2
< 0.1%
53 3
< 0.1%
52 2
< 0.1%
51 3
< 0.1%
50 1
 
< 0.1%
49 1
 
< 0.1%

num_tl_120dpd_2m
Categorical

High correlation  Imbalance  Missing 

Distinct3
Distinct (%)< 0.1%
Missing4592
Missing (%)6.8%
Memory size1.0 MiB
0.0
63194 
1.0
 
34
2.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters189687
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 63194
93.2%
1.0 34
 
0.1%
2.0 1
 
< 0.1%
(Missing) 4592
 
6.8%

Length

2026-01-19T10:07:46.143473image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:46.202577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 63194
99.9%
1.0 34
 
0.1%
2.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 126423
66.6%
. 63229
33.3%
1 34
 
< 0.1%
2 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 189687
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 126423
66.6%
. 63229
33.3%
1 34
 
< 0.1%
2 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 189687
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 126423
66.6%
. 63229
33.3%
1 34
 
< 0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 189687
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 126423
66.6%
. 63229
33.3%
1 34
 
< 0.1%
2 1
 
< 0.1%

num_tl_30dpd
Categorical

High correlation  Imbalance  Missing 

Distinct5
Distinct (%)< 0.1%
Missing2093
Missing (%)3.1%
Memory size1.0 MiB
0.0
65569 
1.0
 
149
2.0
 
7
4.0
 
2
3.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters197184
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 65569
96.7%
1.0 149
 
0.2%
2.0 7
 
< 0.1%
4.0 2
 
< 0.1%
3.0 1
 
< 0.1%
(Missing) 2093
 
3.1%

Length

2026-01-19T10:07:46.265238image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:46.323820image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 65569
99.8%
1.0 149
 
0.2%
2.0 7
 
< 0.1%
4.0 2
 
< 0.1%
3.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 131297
66.6%
. 65728
33.3%
1 149
 
0.1%
2 7
 
< 0.1%
4 2
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 197184
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 131297
66.6%
. 65728
33.3%
1 149
 
0.1%
2 7
 
< 0.1%
4 2
 
< 0.1%
3 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 197184
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 131297
66.6%
. 65728
33.3%
1 149
 
0.1%
2 7
 
< 0.1%
4 2
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 197184
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 131297
66.6%
. 65728
33.3%
1 149
 
0.1%
2 7
 
< 0.1%
4 2
 
< 0.1%
3 1
 
< 0.1%

num_tl_90g_dpd_24m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct18
Distinct (%)< 0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.081091772
Minimum0
Maximum24
Zeros62217
Zeros (%)91.7%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:46.386485image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4696549
Coefficient of variation (CV)5.7916468
Kurtosis343.48507
Mean0.081091772
Median Absolute Deviation (MAD)0
Skewness13.722055
Sum5330
Variance0.22057573
MonotonicityNot monotonic
2026-01-19T10:07:46.452612image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 62217
91.7%
1 2645
 
3.9%
2 514
 
0.8%
3 151
 
0.2%
4 76
 
0.1%
5 42
 
0.1%
6 29
 
< 0.1%
7 18
 
< 0.1%
8 10
 
< 0.1%
9 9
 
< 0.1%
Other values (8) 17
 
< 0.1%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 62217
91.7%
1 2645
 
3.9%
2 514
 
0.8%
3 151
 
0.2%
4 76
 
0.1%
5 42
 
0.1%
6 29
 
< 0.1%
7 18
 
< 0.1%
8 10
 
< 0.1%
9 9
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
20 1
 
< 0.1%
16 2
 
< 0.1%
14 1
 
< 0.1%
13 3
 
< 0.1%
12 4
 
< 0.1%
11 2
 
< 0.1%
10 3
 
< 0.1%
9 9
< 0.1%
8 10
< 0.1%

num_tl_op_past_12m
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct20
Distinct (%)< 0.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean2.0813961
Minimum0
Maximum20
Zeros12386
Zeros (%)18.3%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:46.515717image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8246854
Coefficient of variation (CV)0.87666421
Kurtosis3.6698213
Mean2.0813961
Median Absolute Deviation (MAD)1
Skewness1.4219169
Sum136806
Variance3.3294769
MonotonicityNot monotonic
2026-01-19T10:07:46.589909image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 16715
24.6%
2 14709
21.7%
0 12386
18.3%
3 10009
14.8%
4 5799
 
8.6%
5 2920
 
4.3%
6 1478
 
2.2%
7 821
 
1.2%
8 414
 
0.6%
9 204
 
0.3%
Other values (10) 273
 
0.4%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 12386
18.3%
1 16715
24.6%
2 14709
21.7%
3 10009
14.8%
4 5799
 
8.6%
5 2920
 
4.3%
6 1478
 
2.2%
7 821
 
1.2%
8 414
 
0.6%
9 204
 
0.3%
ValueCountFrequency (%)
20 1
 
< 0.1%
18 3
 
< 0.1%
17 1
 
< 0.1%
16 4
 
< 0.1%
15 7
 
< 0.1%
14 13
 
< 0.1%
13 19
 
< 0.1%
12 42
 
0.1%
11 64
0.1%
10 119
0.2%

pct_tl_nvr_dlq
Real number (ℝ)

High correlation  Missing 

Distinct424
Distinct (%)0.6%
Missing2097
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean94.154723
Minimum0
Maximum100
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:46.672041image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile75
Q191.3
median100
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)8.7

Descriptive statistics

Standard deviation8.9314181
Coefficient of variation (CV)0.09485895
Kurtosis6.8077928
Mean94.154723
Median Absolute Deviation (MAD)0
Skewness-2.2622093
Sum6188225
Variance79.770229
MonotonicityNot monotonic
2026-01-19T10:07:46.756201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 33162
48.9%
90 915
 
1.3%
95 806
 
1.2%
90.9 710
 
1.0%
88.9 705
 
1.0%
96 695
 
1.0%
92.9 692
 
1.0%
87.5 682
 
1.0%
91.7 682
 
1.0%
92.3 679
 
1.0%
Other values (414) 25996
38.3%
(Missing) 2097
 
3.1%
ValueCountFrequency (%)
0 1
< 0.1%
13.3 1
< 0.1%
18 1
< 0.1%
18.2 1
< 0.1%
19 1
< 0.1%
19.2 1
< 0.1%
22.2 2
< 0.1%
23.1 2
< 0.1%
23.8 1
< 0.1%
25 2
< 0.1%
ValueCountFrequency (%)
100 33162
48.9%
99.4 1
 
< 0.1%
99.2 1
 
< 0.1%
99 3
 
< 0.1%
98.9 4
 
< 0.1%
98.8 1
 
< 0.1%
98.7 7
 
< 0.1%
98.6 16
 
< 0.1%
98.5 24
 
< 0.1%
98.4 39
 
0.1%

percent_bc_gt_75
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct142
Distinct (%)0.2%
Missing2214
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean42.515292
Minimum0
Maximum100
Zeros17924
Zeros (%)26.4%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:46.838351image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median37.5
Q371.4
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)71.4

Descriptive statistics

Standard deviation36.233203
Coefficient of variation (CV)0.85223931
Kurtosis-1.2575788
Mean42.515292
Median Absolute Deviation (MAD)37.5
Skewness0.30743544
Sum2789300.8
Variance1312.845
MonotonicityNot monotonic
2026-01-19T10:07:46.921511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17924
26.4%
100 11260
16.6%
50 6876
 
10.1%
33.3 4487
 
6.6%
66.7 4107
 
6.1%
25 2995
 
4.4%
75 2280
 
3.4%
20 1966
 
2.9%
40 1690
 
2.5%
60 1401
 
2.1%
Other values (132) 10621
15.7%
(Missing) 2214
 
3.3%
ValueCountFrequency (%)
0 17924
26.4%
0.25 1
 
< 0.1%
0.33 1
 
< 0.1%
0.5 2
 
< 0.1%
0.67 2
 
< 0.1%
0.75 1
 
< 0.1%
1 7
 
< 0.1%
3.6 1
 
< 0.1%
4.2 1
 
< 0.1%
4.3 1
 
< 0.1%
ValueCountFrequency (%)
100 11260
16.6%
94.1 1
 
< 0.1%
93.8 1
 
< 0.1%
93.3 2
 
< 0.1%
92.9 3
 
< 0.1%
92.3 4
 
< 0.1%
91.7 14
 
< 0.1%
90.9 22
 
< 0.1%
90 49
 
0.1%
88.9 84
 
0.1%

pub_rec_bankruptcies
Real number (ℝ)

High correlation  Zeros 

Distinct8
Distinct (%)< 0.1%
Missing38
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.12787867
Minimum0
Maximum7
Zeros59640
Zeros (%)87.9%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:46.985126image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.36538965
Coefficient of variation (CV)2.8573151
Kurtosis19.752638
Mean0.12787867
Median Absolute Deviation (MAD)0
Skewness3.4720923
Sum8668
Variance0.1335096
MonotonicityNot monotonic
2026-01-19T10:07:47.045275image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 59640
87.9%
1 7762
 
11.4%
2 289
 
0.4%
3 59
 
0.1%
4 18
 
< 0.1%
5 12
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
(Missing) 38
 
0.1%
ValueCountFrequency (%)
0 59640
87.9%
1 7762
 
11.4%
2 289
 
0.4%
3 59
 
0.1%
4 18
 
< 0.1%
5 12
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 2
 
< 0.1%
5 12
 
< 0.1%
4 18
 
< 0.1%
3 59
 
0.1%
2 289
 
0.4%
1 7762
 
11.4%
0 59640
87.9%

tax_liens
Real number (ℝ)

Zeros 

Distinct15
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.046846661
Minimum0
Maximum23
Zeros65845
Zeros (%)97.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:47.105508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.36222984
Coefficient of variation (CV)7.7322445
Kurtosis595.67433
Mean0.046846661
Median Absolute Deviation (MAD)0
Skewness17.61587
Sum3177
Variance0.13121045
MonotonicityNot monotonic
2026-01-19T10:07:47.167120image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 65845
97.1%
1 1361
 
2.0%
2 357
 
0.5%
3 124
 
0.2%
4 63
 
0.1%
5 25
 
< 0.1%
6 17
 
< 0.1%
7 6
 
< 0.1%
10 5
 
< 0.1%
9 5
 
< 0.1%
Other values (5) 9
 
< 0.1%
ValueCountFrequency (%)
0 65845
97.1%
1 1361
 
2.0%
2 357
 
0.5%
3 124
 
0.2%
4 63
 
0.1%
5 25
 
< 0.1%
6 17
 
< 0.1%
7 6
 
< 0.1%
8 4
 
< 0.1%
9 5
 
< 0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
18 2
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
10 5
 
< 0.1%
9 5
 
< 0.1%
8 4
 
< 0.1%
7 6
 
< 0.1%
6 17
< 0.1%
5 25
< 0.1%

tot_hi_cred_lim
Real number (ℝ)

High correlation  Missing 

Distinct53962
Distinct (%)82.1%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean179106.34
Minimum0
Maximum9999999
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:47.242691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18602.35
Q150775
median116076
Q3257372.25
95-th percentile514240.1
Maximum9999999
Range9999999
Interquartile range (IQR)206597.25

Descriptive statistics

Standard deviation188063.42
Coefficient of variation (CV)1.0500098
Kurtosis244.42181
Mean179106.34
Median Absolute Deviation (MAD)80373.5
Skewness6.7596843
Sum1.1772301 × 1010
Variance3.5367848 × 1010
MonotonicityNot monotonic
2026-01-19T10:07:47.326730image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16500 28
 
< 0.1%
19300 28
 
< 0.1%
15500 27
 
< 0.1%
9000 26
 
< 0.1%
15000 26
 
< 0.1%
10700 26
 
< 0.1%
14800 26
 
< 0.1%
12600 25
 
< 0.1%
11000 25
 
< 0.1%
17500 25
 
< 0.1%
Other values (53952) 65466
96.5%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 3
 
< 0.1%
300 3
 
< 0.1%
400 1
 
< 0.1%
500 9
< 0.1%
800 2
 
< 0.1%
900 1
 
< 0.1%
1000 5
< 0.1%
1100 1
 
< 0.1%
1200 1
 
< 0.1%
1300 1
 
< 0.1%
ValueCountFrequency (%)
9999999 2
< 0.1%
4562297 1
< 0.1%
4460960 1
< 0.1%
2695475 1
< 0.1%
2676157 1
< 0.1%
2646039 1
< 0.1%
2575022 1
< 0.1%
2574225 1
< 0.1%
2548791 1
< 0.1%
2532616 1
< 0.1%

total_bal_ex_mort
Real number (ℝ)

High correlation  Missing 

Distinct49187
Distinct (%)74.1%
Missing1485
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean51304.858
Minimum0
Maximum1164872
Zeros54
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:47.405849image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6679
Q121002.75
median38086.5
Q364980
95-th percentile139827
Maximum1164872
Range1164872
Interquartile range (IQR)43977.25

Descriptive statistics

Standard deviation49698.496
Coefficient of variation (CV)0.96868986
Kurtosis28.489313
Mean51304.858
Median Absolute Deviation (MAD)20139
Skewness3.6021457
Sum3.4033591 × 109
Variance2.4699405 × 109
MonotonicityNot monotonic
2026-01-19T10:07:47.486497image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 54
 
0.1%
26452 8
 
< 0.1%
23210 7
 
< 0.1%
12325 7
 
< 0.1%
7455 7
 
< 0.1%
16599 6
 
< 0.1%
20084 6
 
< 0.1%
8673 6
 
< 0.1%
7704 6
 
< 0.1%
39425 6
 
< 0.1%
Other values (49177) 66223
97.6%
(Missing) 1485
 
2.2%
ValueCountFrequency (%)
0 54
0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
8 2
 
< 0.1%
9 3
 
< 0.1%
17 1
 
< 0.1%
20 1
 
< 0.1%
27 2
 
< 0.1%
38 3
 
< 0.1%
39 1
 
< 0.1%
ValueCountFrequency (%)
1164872 1
< 0.1%
1072366 1
< 0.1%
930478 1
< 0.1%
927734 1
< 0.1%
845977 1
< 0.1%
815010 1
< 0.1%
777866 1
< 0.1%
767381 1
< 0.1%
720812 1
< 0.1%
710000 1
< 0.1%

total_bc_limit
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct2461
Distinct (%)3.7%
Missing1485
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean23180.708
Minimum0
Maximum616000
Zeros729
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:47.567702image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2300
Q18200
median16300
Q330200
95-th percentile67100
Maximum616000
Range616000
Interquartile range (IQR)22000

Descriptive statistics

Standard deviation23219.685
Coefficient of variation (CV)1.0016815
Kurtosis24.460855
Mean23180.708
Median Absolute Deviation (MAD)9600
Skewness3.1407279
Sum1.5377154 × 109
Variance5.3915379 × 108
MonotonicityNot monotonic
2026-01-19T10:07:47.650332image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 729
 
1.1%
5000 512
 
0.8%
6000 472
 
0.7%
8000 441
 
0.7%
4000 435
 
0.6%
10000 431
 
0.6%
3000 426
 
0.6%
9000 418
 
0.6%
6500 415
 
0.6%
7500 407
 
0.6%
Other values (2451) 61650
90.9%
(Missing) 1485
 
2.2%
ValueCountFrequency (%)
0 729
1.1%
200 10
 
< 0.1%
300 72
 
0.1%
400 18
 
< 0.1%
500 217
 
0.3%
600 45
 
0.1%
700 50
 
0.1%
800 149
 
0.2%
900 33
 
< 0.1%
950 1
 
< 0.1%
ValueCountFrequency (%)
616000 1
< 0.1%
471400 1
< 0.1%
470900 1
< 0.1%
372800 1
< 0.1%
368500 1
< 0.1%
364000 1
< 0.1%
339900 1
< 0.1%
333900 1
< 0.1%
329200 1
< 0.1%
319800 1
< 0.1%

total_il_high_credit_limit
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct40887
Distinct (%)62.2%
Missing2093
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean44009.529
Minimum0
Maximum976075
Zeros7816
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:47.735558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115000
median32896
Q359382.25
95-th percentile125271.95
Maximum976075
Range976075
Interquartile range (IQR)44382.25

Descriptive statistics

Standard deviation45033.543
Coefficient of variation (CV)1.023268
Kurtosis17.141804
Mean44009.529
Median Absolute Deviation (MAD)20896
Skewness2.8154222
Sum2.8926583 × 109
Variance2.02802 × 109
MonotonicityNot monotonic
2026-01-19T10:07:47.817755image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7816
 
11.5%
10000 418
 
0.6%
15000 326
 
0.5%
20000 239
 
0.4%
5000 228
 
0.3%
25000 191
 
0.3%
12000 187
 
0.3%
6000 169
 
0.2%
8000 140
 
0.2%
18000 114
 
0.2%
Other values (40877) 55900
82.4%
(Missing) 2093
 
3.1%
ValueCountFrequency (%)
0 7816
11.5%
300 1
 
< 0.1%
336 1
 
< 0.1%
449 1
 
< 0.1%
450 1
 
< 0.1%
451 1
 
< 0.1%
494 1
 
< 0.1%
500 10
 
< 0.1%
520 1
 
< 0.1%
550 1
 
< 0.1%
ValueCountFrequency (%)
976075 1
< 0.1%
818478 1
< 0.1%
637503 1
< 0.1%
602777 1
< 0.1%
601737 1
< 0.1%
597620 1
< 0.1%
589824 1
< 0.1%
557098 1
< 0.1%
551499 1
< 0.1%
550598 1
< 0.1%

revol_bal_joint
Real number (ℝ)

High correlation  Missing 

Distinct3161
Distinct (%)97.3%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean32957.47
Minimum0
Maximum326249
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:48.028040image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5138.4
Q114690
median25717
Q343471
95-th percentile84003.4
Maximum326249
Range326249
Interquartile range (IQR)28781

Descriptive statistics

Standard deviation27381.251
Coefficient of variation (CV)0.8308056
Kurtosis9.766907
Mean32957.47
Median Absolute Deviation (MAD)13015
Skewness2.3104107
Sum1.0707882 × 108
Variance7.497329 × 108
MonotonicityNot monotonic
2026-01-19T10:07:48.106279image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
< 0.1%
38073 3
 
< 0.1%
23871 3
 
< 0.1%
35762 2
 
< 0.1%
19048 2
 
< 0.1%
26547 2
 
< 0.1%
49046 2
 
< 0.1%
26994 2
 
< 0.1%
48508 2
 
< 0.1%
27263 2
 
< 0.1%
Other values (3151) 3225
 
4.8%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 4
< 0.1%
12 1
 
< 0.1%
42 1
 
< 0.1%
139 1
 
< 0.1%
206 1
 
< 0.1%
297 1
 
< 0.1%
311 1
 
< 0.1%
331 1
 
< 0.1%
350 1
 
< 0.1%
408 1
 
< 0.1%
ValueCountFrequency (%)
326249 1
< 0.1%
234894 1
< 0.1%
204796 1
< 0.1%
200504 1
< 0.1%
190137 1
< 0.1%
189004 1
< 0.1%
187688 1
< 0.1%
187186 1
< 0.1%
180108 1
< 0.1%
178871 1
< 0.1%

sec_app_fico_range_low
Real number (ℝ)

High correlation  Missing 

Distinct57
Distinct (%)1.8%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean670.54171
Minimum540
Maximum820
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:48.182925image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum540
5-th percentile590
Q1645
median670
Q3700
95-th percentile745
Maximum820
Range280
Interquartile range (IQR)55

Descriptive statistics

Standard deviation45.445241
Coefficient of variation (CV)0.067773921
Kurtosis0.49359377
Mean670.54171
Median Absolute Deviation (MAD)25
Skewness0.035579844
Sum2178590
Variance2065.2699
MonotonicityNot monotonic
2026-01-19T10:07:48.259063image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660 181
 
0.3%
670 169
 
0.2%
665 167
 
0.2%
675 163
 
0.2%
655 159
 
0.2%
685 148
 
0.2%
680 148
 
0.2%
695 136
 
0.2%
650 130
 
0.2%
645 129
 
0.2%
Other values (47) 1719
 
2.5%
(Missing) 64572
95.2%
ValueCountFrequency (%)
540 8
 
< 0.1%
545 5
 
< 0.1%
550 10
< 0.1%
555 12
< 0.1%
560 12
< 0.1%
565 16
< 0.1%
570 14
< 0.1%
575 14
< 0.1%
580 22
< 0.1%
585 24
< 0.1%
ValueCountFrequency (%)
820 2
 
< 0.1%
815 4
 
< 0.1%
810 2
 
< 0.1%
805 4
 
< 0.1%
800 6
< 0.1%
795 10
< 0.1%
790 12
< 0.1%
785 6
< 0.1%
780 12
< 0.1%
775 10
< 0.1%

sec_app_fico_range_high
Real number (ℝ)

High correlation  Missing 

Distinct57
Distinct (%)1.8%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean674.54171
Minimum544
Maximum824
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:48.334222image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum544
5-th percentile594
Q1649
median674
Q3704
95-th percentile749
Maximum824
Range280
Interquartile range (IQR)55

Descriptive statistics

Standard deviation45.445241
Coefficient of variation (CV)0.067372025
Kurtosis0.49359377
Mean674.54171
Median Absolute Deviation (MAD)25
Skewness0.035579844
Sum2191586
Variance2065.2699
MonotonicityNot monotonic
2026-01-19T10:07:48.412154image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
664 181
 
0.3%
674 169
 
0.2%
669 167
 
0.2%
679 163
 
0.2%
659 159
 
0.2%
689 148
 
0.2%
684 148
 
0.2%
699 136
 
0.2%
654 130
 
0.2%
649 129
 
0.2%
Other values (47) 1719
 
2.5%
(Missing) 64572
95.2%
ValueCountFrequency (%)
544 8
 
< 0.1%
549 5
 
< 0.1%
554 10
< 0.1%
559 12
< 0.1%
564 12
< 0.1%
569 16
< 0.1%
574 14
< 0.1%
579 14
< 0.1%
584 22
< 0.1%
589 24
< 0.1%
ValueCountFrequency (%)
824 2
 
< 0.1%
819 4
 
< 0.1%
814 2
 
< 0.1%
809 4
 
< 0.1%
804 6
< 0.1%
799 10
< 0.1%
794 12
< 0.1%
789 6
< 0.1%
784 12
< 0.1%
779 10
< 0.1%
Distinct454
Distinct (%)14.0%
Missing64572
Missing (%)95.2%
Memory size1.0 MiB
Minimum1959-01-01 00:00:00
Maximum2017-10-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:48.490298image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:48.580968image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

sec_app_inq_last_6mths
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct7
Distinct (%)0.2%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean0.6303478
Minimum0
Maximum6
Zeros1988
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:48.651065image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0145262
Coefficient of variation (CV)1.6094706
Kurtosis5.2170576
Mean0.6303478
Median Absolute Deviation (MAD)0
Skewness2.1225421
Sum2048
Variance1.0292635
MonotonicityNot monotonic
2026-01-19T10:07:48.708213image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1988
 
2.9%
1 793
 
1.2%
2 281
 
0.4%
3 104
 
0.2%
4 40
 
0.1%
5 37
 
0.1%
6 6
 
< 0.1%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 1988
2.9%
1 793
 
1.2%
2 281
 
0.4%
3 104
 
0.2%
4 40
 
0.1%
5 37
 
0.1%
6 6
 
< 0.1%
ValueCountFrequency (%)
6 6
 
< 0.1%
5 37
 
0.1%
4 40
 
0.1%
3 104
 
0.2%
2 281
 
0.4%
1 793
 
1.2%
0 1988
2.9%

sec_app_mort_acc
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct13
Distinct (%)0.4%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean1.4801477
Minimum0
Maximum12
Zeros1332
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:48.767856image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7285784
Coefficient of variation (CV)1.1678418
Kurtosis2.0374336
Mean1.4801477
Median Absolute Deviation (MAD)1
Skewness1.3463918
Sum4809
Variance2.9879832
MonotonicityNot monotonic
2026-01-19T10:07:48.835963image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1332
 
2.0%
1 622
 
0.9%
2 522
 
0.8%
3 341
 
0.5%
4 202
 
0.3%
5 140
 
0.2%
6 52
 
0.1%
7 23
 
< 0.1%
8 6
 
< 0.1%
10 3
 
< 0.1%
Other values (3) 6
 
< 0.1%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 1332
2.0%
1 622
0.9%
2 522
 
0.8%
3 341
 
0.5%
4 202
 
0.3%
5 140
 
0.2%
6 52
 
0.1%
7 23
 
< 0.1%
8 6
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 2
 
< 0.1%
10 3
 
< 0.1%
9 3
 
< 0.1%
8 6
 
< 0.1%
7 23
 
< 0.1%
6 52
 
0.1%
5 140
0.2%
4 202
0.3%
3 341
0.5%

sec_app_open_acc
Real number (ℝ)

High correlation  Missing 

Distinct49
Distinct (%)1.5%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean11.588181
Minimum0
Maximum53
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:48.907719image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q17
median10
Q315
95-th percentile24
Maximum53
Range53
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.8162681
Coefficient of variation (CV)0.58820863
Kurtosis2.5201735
Mean11.588181
Median Absolute Deviation (MAD)4
Skewness1.2176392
Sum37650
Variance46.461511
MonotonicityNot monotonic
2026-01-19T10:07:48.988943image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
9 240
 
0.4%
10 228
 
0.3%
8 226
 
0.3%
7 215
 
0.3%
11 207
 
0.3%
5 193
 
0.3%
6 187
 
0.3%
13 183
 
0.3%
12 173
 
0.3%
4 141
 
0.2%
Other values (39) 1256
 
1.9%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 45
 
0.1%
2 85
 
0.1%
3 105
0.2%
4 141
0.2%
5 193
0.3%
6 187
0.3%
7 215
0.3%
8 226
0.3%
9 240
0.4%
ValueCountFrequency (%)
53 1
 
< 0.1%
51 1
 
< 0.1%
49 1
 
< 0.1%
48 1
 
< 0.1%
45 1
 
< 0.1%
44 1
 
< 0.1%
42 3
< 0.1%
41 1
 
< 0.1%
40 1
 
< 0.1%
39 4
< 0.1%

sec_app_revol_util
Real number (ℝ)

High correlation  Missing 

Distinct939
Distinct (%)29.4%
Missing64629
Missing (%)95.3%
Infinite0
Infinite (%)0.0%
Mean58.016667
Minimum0
Maximum156
Zeros34
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:49.065563image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.4
Q139.875
median60.5
Q377.825
95-th percentile96
Maximum156
Range156
Interquartile range (IQR)37.95

Descriptive statistics

Standard deviation25.412534
Coefficient of variation (CV)0.43802127
Kurtosis-0.61939299
Mean58.016667
Median Absolute Deviation (MAD)18.8
Skewness-0.2700831
Sum185189.2
Variance645.79688
MonotonicityNot monotonic
2026-01-19T10:07:49.149227image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34
 
0.1%
61.3 13
 
< 0.1%
73.4 12
 
< 0.1%
62.6 11
 
< 0.1%
64.1 11
 
< 0.1%
69.5 10
 
< 0.1%
52.8 10
 
< 0.1%
97 9
 
< 0.1%
65.4 9
 
< 0.1%
74.7 9
 
< 0.1%
Other values (929) 3064
 
4.5%
(Missing) 64629
95.3%
ValueCountFrequency (%)
0 34
0.1%
0.3 3
 
< 0.1%
0.4 1
 
< 0.1%
0.5 1
 
< 0.1%
0.6 5
 
< 0.1%
0.8 1
 
< 0.1%
0.9 1
 
< 0.1%
1 3
 
< 0.1%
1.1 1
 
< 0.1%
1.2 1
 
< 0.1%
ValueCountFrequency (%)
156 1
< 0.1%
140.8 1
< 0.1%
127.2 1
< 0.1%
124.8 1
< 0.1%
110.6 1
< 0.1%
106.9 1
< 0.1%
106.8 1
< 0.1%
106.4 1
< 0.1%
105.6 2
< 0.1%
105.1 1
< 0.1%

sec_app_open_act_il
Real number (ℝ)

High correlation  Missing 

Distinct29
Distinct (%)0.9%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean3.091105
Minimum0
Maximum32
Zeros408
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:49.227424image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile10
Maximum32
Range32
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.4289513
Coefficient of variation (CV)1.1092963
Kurtosis12.16627
Mean3.091105
Median Absolute Deviation (MAD)1
Skewness2.8903987
Sum10043
Variance11.757707
MonotonicityNot monotonic
2026-01-19T10:07:49.296541image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 725
 
1.1%
2 715
 
1.1%
3 496
 
0.7%
0 408
 
0.6%
4 288
 
0.4%
5 171
 
0.3%
6 103
 
0.2%
7 75
 
0.1%
8 53
 
0.1%
9 45
 
0.1%
Other values (19) 170
 
0.3%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 408
0.6%
1 725
1.1%
2 715
1.1%
3 496
0.7%
4 288
 
0.4%
5 171
 
0.3%
6 103
 
0.2%
7 75
 
0.1%
8 53
 
0.1%
9 45
 
0.1%
ValueCountFrequency (%)
32 1
 
< 0.1%
30 2
 
< 0.1%
29 1
 
< 0.1%
25 3
< 0.1%
24 2
 
< 0.1%
23 1
 
< 0.1%
22 4
< 0.1%
21 5
< 0.1%
20 2
 
< 0.1%
19 6
< 0.1%

sec_app_num_rev_accts
Real number (ℝ)

High correlation  Missing 

Distinct57
Distinct (%)1.8%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean12.611265
Minimum0
Maximum95
Zeros19
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:49.372206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median11
Q317
95-th percentile28
Maximum95
Range95
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.2932333
Coefficient of variation (CV)0.65760519
Kurtosis5.0533407
Mean12.611265
Median Absolute Deviation (MAD)5
Skewness1.4920467
Sum40974
Variance68.777718
MonotonicityNot monotonic
2026-01-19T10:07:49.447831image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 201
 
0.3%
8 197
 
0.3%
9 195
 
0.3%
6 191
 
0.3%
7 190
 
0.3%
12 169
 
0.2%
13 166
 
0.2%
5 162
 
0.2%
11 146
 
0.2%
4 142
 
0.2%
Other values (47) 1490
 
2.2%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 19
 
< 0.1%
1 56
 
0.1%
2 92
0.1%
3 117
0.2%
4 142
0.2%
5 162
0.2%
6 191
0.3%
7 190
0.3%
8 197
0.3%
9 195
0.3%
ValueCountFrequency (%)
95 1
< 0.1%
64 1
< 0.1%
56 1
< 0.1%
54 1
< 0.1%
53 1
< 0.1%
51 1
< 0.1%
50 1
< 0.1%
49 2
< 0.1%
48 1
< 0.1%
47 1
< 0.1%

sec_app_chargeoff_within_12_mths
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct9
Distinct (%)0.3%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean0.040935673
Minimum0
Maximum11
Zeros3159
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:49.510928image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3427448
Coefficient of variation (CV)8.3727659
Kurtosis431.96519
Mean0.040935673
Median Absolute Deviation (MAD)0
Skewness17.5057
Sum133
Variance0.117474
MonotonicityNot monotonic
2026-01-19T10:07:49.571612image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3159
 
4.7%
1 74
 
0.1%
2 8
 
< 0.1%
4 2
 
< 0.1%
3 2
 
< 0.1%
11 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 3159
4.7%
1 74
 
0.1%
2 8
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 2
 
< 0.1%
2 8
 
< 0.1%
1 74
 
0.1%
0 3159
4.7%

sec_app_collections_12_mths_ex_med
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct7
Distinct (%)0.2%
Missing64572
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean0.084025854
Minimum0
Maximum6
Zeros3057
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:49.625201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.40549677
Coefficient of variation (CV)4.8258572
Kurtosis74.830679
Mean0.084025854
Median Absolute Deviation (MAD)0
Skewness7.4225958
Sum273
Variance0.16442763
MonotonicityNot monotonic
2026-01-19T10:07:49.684291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 3057
 
4.5%
1 144
 
0.2%
2 32
 
< 0.1%
3 7
 
< 0.1%
4 4
 
< 0.1%
6 3
 
< 0.1%
5 2
 
< 0.1%
(Missing) 64572
95.2%
ValueCountFrequency (%)
0 3057
4.5%
1 144
 
0.2%
2 32
 
< 0.1%
3 7
 
< 0.1%
4 4
 
< 0.1%
5 2
 
< 0.1%
6 3
 
< 0.1%
ValueCountFrequency (%)
6 3
 
< 0.1%
5 2
 
< 0.1%
4 4
 
< 0.1%
3 7
 
< 0.1%
2 32
 
< 0.1%
1 144
 
0.2%
0 3057
4.5%

sec_app_mths_since_last_major_derog
Real number (ℝ)

High correlation  Missing 

Distinct94
Distinct (%)8.9%
Missing66766
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean36.224645
Minimum0
Maximum115
Zeros9
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:49.757921image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q115
median34
Q355
95-th percentile76
Maximum115
Range115
Interquartile range (IQR)40

Descriptive statistics

Standard deviation24.1
Coefficient of variation (CV)0.66529294
Kurtosis-0.79939797
Mean36.224645
Median Absolute Deviation (MAD)20
Skewness0.3169506
Sum38217
Variance580.81002
MonotonicityNot monotonic
2026-01-19T10:07:49.840080image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 39
 
0.1%
8 24
 
< 0.1%
2 23
 
< 0.1%
48 22
 
< 0.1%
47 20
 
< 0.1%
17 19
 
< 0.1%
29 19
 
< 0.1%
11 18
 
< 0.1%
68 18
 
< 0.1%
13 17
 
< 0.1%
Other values (84) 836
 
1.2%
(Missing) 66766
98.4%
ValueCountFrequency (%)
0 9
 
< 0.1%
1 39
0.1%
2 23
< 0.1%
3 16
< 0.1%
4 14
 
< 0.1%
5 13
 
< 0.1%
6 12
 
< 0.1%
7 17
< 0.1%
8 24
< 0.1%
9 15
 
< 0.1%
ValueCountFrequency (%)
115 1
< 0.1%
114 1
< 0.1%
113 1
< 0.1%
107 1
< 0.1%
103 1
< 0.1%
97 1
< 0.1%
93 1
< 0.1%
88 1
< 0.1%
85 1
< 0.1%
84 1
< 0.1%

hardship_flag
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size596.1 KiB
False
67793 
True
 
28
ValueCountFrequency (%)
False 67793
> 99.9%
True 28
 
< 0.1%
2026-01-19T10:07:49.905247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

hardship_type
Categorical

Constant  Missing 

Distinct1
Distinct (%)0.3%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
INTEREST ONLY-3 MONTHS DEFERRAL
334 

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters10354
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowINTEREST ONLY-3 MONTHS DEFERRAL
2nd rowINTEREST ONLY-3 MONTHS DEFERRAL
3rd rowINTEREST ONLY-3 MONTHS DEFERRAL
4th rowINTEREST ONLY-3 MONTHS DEFERRAL
5th rowINTEREST ONLY-3 MONTHS DEFERRAL

Common Values

ValueCountFrequency (%)
INTEREST ONLY-3 MONTHS DEFERRAL 334
 
0.5%
(Missing) 67487
99.5%

Length

2026-01-19T10:07:49.967881image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:50.020446image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
interest 334
25.0%
only-3 334
25.0%
months 334
25.0%
deferral 334
25.0%

Most occurring characters

ValueCountFrequency (%)
E 1336
12.9%
1002
9.7%
N 1002
9.7%
T 1002
9.7%
R 1002
9.7%
O 668
 
6.5%
S 668
 
6.5%
L 668
 
6.5%
I 334
 
3.2%
Y 334
 
3.2%
Other values (7) 2338
22.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10354
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 1336
12.9%
1002
9.7%
N 1002
9.7%
T 1002
9.7%
R 1002
9.7%
O 668
 
6.5%
S 668
 
6.5%
L 668
 
6.5%
I 334
 
3.2%
Y 334
 
3.2%
Other values (7) 2338
22.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10354
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 1336
12.9%
1002
9.7%
N 1002
9.7%
T 1002
9.7%
R 1002
9.7%
O 668
 
6.5%
S 668
 
6.5%
L 668
 
6.5%
I 334
 
3.2%
Y 334
 
3.2%
Other values (7) 2338
22.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10354
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 1336
12.9%
1002
9.7%
N 1002
9.7%
T 1002
9.7%
R 1002
9.7%
O 668
 
6.5%
S 668
 
6.5%
L 668
 
6.5%
I 334
 
3.2%
Y 334
 
3.2%
Other values (7) 2338
22.6%

hardship_reason
Categorical

High correlation  Missing 

Distinct9
Distinct (%)2.7%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
NATURAL_DISASTER
98 
EXCESSIVE_OBLIGATIONS
73 
UNEMPLOYMENT
57 
MEDICAL
38 
INCOME_CURTAILMENT
33 
Other values (4)
35 

Length

Max length21
Median length18
Mean length15.080838
Min length7

Characters and Unicode

Total characters5037
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEXCESSIVE_OBLIGATIONS
2nd rowEXCESSIVE_OBLIGATIONS
3rd rowEXCESSIVE_OBLIGATIONS
4th rowEXCESSIVE_OBLIGATIONS
5th rowNATURAL_DISASTER

Common Values

ValueCountFrequency (%)
NATURAL_DISASTER 98
 
0.1%
EXCESSIVE_OBLIGATIONS 73
 
0.1%
UNEMPLOYMENT 57
 
0.1%
MEDICAL 38
 
0.1%
INCOME_CURTAILMENT 33
 
< 0.1%
REDUCED_HOURS 17
 
< 0.1%
DIVORCE 7
 
< 0.1%
FAMILY_DEATH 6
 
< 0.1%
DISABILITY 5
 
< 0.1%
(Missing) 67487
99.5%

Length

2026-01-19T10:07:50.083624image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:50.156805image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
natural_disaster 98
29.3%
excessive_obligations 73
21.9%
unemployment 57
17.1%
medical 38
 
11.4%
income_curtailment 33
 
9.9%
reduced_hours 17
 
5.1%
divorce 7
 
2.1%
family_death 6
 
1.8%
disability 5
 
1.5%

Most occurring characters

ValueCountFrequency (%)
E 582
11.6%
A 455
 
9.0%
I 449
 
8.9%
S 437
 
8.7%
T 403
 
8.0%
N 351
 
7.0%
L 310
 
6.2%
R 270
 
5.4%
O 260
 
5.2%
_ 227
 
4.5%
Other values (12) 1293
25.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5037
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 582
11.6%
A 455
 
9.0%
I 449
 
8.9%
S 437
 
8.7%
T 403
 
8.0%
N 351
 
7.0%
L 310
 
6.2%
R 270
 
5.4%
O 260
 
5.2%
_ 227
 
4.5%
Other values (12) 1293
25.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5037
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 582
11.6%
A 455
 
9.0%
I 449
 
8.9%
S 437
 
8.7%
T 403
 
8.0%
N 351
 
7.0%
L 310
 
6.2%
R 270
 
5.4%
O 260
 
5.2%
_ 227
 
4.5%
Other values (12) 1293
25.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5037
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 582
11.6%
A 455
 
9.0%
I 449
 
8.9%
S 437
 
8.7%
T 403
 
8.0%
N 351
 
7.0%
L 310
 
6.2%
R 270
 
5.4%
O 260
 
5.2%
_ 227
 
4.5%
Other values (12) 1293
25.7%

hardship_status
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.9%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
COMPLETED
250 
BROKEN
56 
ACTIVE
28 

Length

Max length9
Median length9
Mean length8.245509
Min length6

Characters and Unicode

Total characters2754
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCOMPLETED
2nd rowBROKEN
3rd rowACTIVE
4th rowCOMPLETED
5th rowCOMPLETED

Common Values

ValueCountFrequency (%)
COMPLETED 250
 
0.4%
BROKEN 56
 
0.1%
ACTIVE 28
 
< 0.1%
(Missing) 67487
99.5%

Length

2026-01-19T10:07:50.249513image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:50.309617image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
completed 250
74.9%
broken 56
 
16.8%
active 28
 
8.4%

Most occurring characters

ValueCountFrequency (%)
E 584
21.2%
O 306
11.1%
C 278
10.1%
T 278
10.1%
M 250
9.1%
L 250
9.1%
P 250
9.1%
D 250
9.1%
B 56
 
2.0%
R 56
 
2.0%
Other values (5) 196
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2754
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 584
21.2%
O 306
11.1%
C 278
10.1%
T 278
10.1%
M 250
9.1%
L 250
9.1%
P 250
9.1%
D 250
9.1%
B 56
 
2.0%
R 56
 
2.0%
Other values (5) 196
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2754
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 584
21.2%
O 306
11.1%
C 278
10.1%
T 278
10.1%
M 250
9.1%
L 250
9.1%
P 250
9.1%
D 250
9.1%
B 56
 
2.0%
R 56
 
2.0%
Other values (5) 196
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2754
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 584
21.2%
O 306
11.1%
C 278
10.1%
T 278
10.1%
M 250
9.1%
L 250
9.1%
P 250
9.1%
D 250
9.1%
B 56
 
2.0%
R 56
 
2.0%
Other values (5) 196
 
7.1%

deferral_term
Categorical

Constant  Missing 

Distinct1
Distinct (%)0.3%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
3.0
334 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1002
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row3.0
3rd row3.0
4th row3.0
5th row3.0

Common Values

ValueCountFrequency (%)
3.0 334
 
0.5%
(Missing) 67487
99.5%

Length

2026-01-19T10:07:50.376241image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:50.427933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
3.0 334
100.0%

Most occurring characters

ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1002
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1002
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1002
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

hardship_amount
Real number (ℝ)

High correlation  Missing 

Distinct332
Distinct (%)99.4%
Missing67487
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean151.60117
Minimum3.73
Maximum790.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:50.488536image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum3.73
5-th percentile17.894
Q155.18
median109.895
Q3206.4
95-th percentile443.5905
Maximum790.68
Range786.95
Interquartile range (IQR)151.22

Descriptive statistics

Standard deviation130.28543
Coefficient of variation (CV)0.85939595
Kurtosis2.6398482
Mean151.60117
Median Absolute Deviation (MAD)63.95
Skewness1.5405323
Sum50634.79
Variance16974.293
MonotonicityNot monotonic
2026-01-19T10:07:50.578699image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80.78 2
 
< 0.1%
229.74 2
 
< 0.1%
357.76 1
 
< 0.1%
187.88 1
 
< 0.1%
87.21 1
 
< 0.1%
46.13 1
 
< 0.1%
126.8 1
 
< 0.1%
222.48 1
 
< 0.1%
113.6 1
 
< 0.1%
175.4 1
 
< 0.1%
Other values (322) 322
 
0.5%
(Missing) 67487
99.5%
ValueCountFrequency (%)
3.73 1
< 0.1%
5.63 1
< 0.1%
9.79 1
< 0.1%
10.49 1
< 0.1%
11.57 1
< 0.1%
11.61 1
< 0.1%
11.76 1
< 0.1%
11.81 1
< 0.1%
12.29 1
< 0.1%
12.52 1
< 0.1%
ValueCountFrequency (%)
790.68 1
< 0.1%
633.21 1
< 0.1%
616.59 1
< 0.1%
549.68 1
< 0.1%
544.78 1
< 0.1%
505.51 1
< 0.1%
503.74 1
< 0.1%
490.71 1
< 0.1%
487.56 1
< 0.1%
487.4 1
< 0.1%

hardship_start_date
Date

Missing 

Distinct24
Distinct (%)7.2%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
Minimum2017-04-01 00:00:00
Maximum2019-03-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:50.651850image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:50.720463image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

hardship_end_date
Date

Missing 

Distinct26
Distinct (%)7.8%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
Minimum2017-05-01 00:00:00
Maximum2019-06-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:50.793591image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:50.866246image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
Distinct25
Distinct (%)7.5%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
Minimum2017-04-01 00:00:00
Maximum2019-04-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:51.068538image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:51.139647image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

hardship_length
Categorical

Constant  Missing 

Distinct1
Distinct (%)0.3%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
3.0
334 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1002
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row3.0
3rd row3.0
4th row3.0
5th row3.0

Common Values

ValueCountFrequency (%)
3.0 334
 
0.5%
(Missing) 67487
99.5%

Length

2026-01-19T10:07:51.218758image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:51.272886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
3.0 334
100.0%

Most occurring characters

ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1002
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1002
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1002
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 334
33.3%
. 334
33.3%
0 334
33.3%

hardship_dpd
Real number (ℝ)

High correlation  Missing 

Distinct31
Distinct (%)9.3%
Missing67487
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean12.781437
Minimum0
Maximum30
Zeros88
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:51.326440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median13
Q321.75
95-th percentile28
Maximum30
Range30
Interquartile range (IQR)21.75

Descriptive statistics

Standard deviation9.9755023
Coefficient of variation (CV)0.78046797
Kurtosis-1.3759806
Mean12.781437
Median Absolute Deviation (MAD)10
Skewness0.021888388
Sum4269
Variance99.510645
MonotonicityNot monotonic
2026-01-19T10:07:51.397055image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 88
 
0.1%
13 15
 
< 0.1%
15 14
 
< 0.1%
21 14
 
< 0.1%
11 14
 
< 0.1%
28 13
 
< 0.1%
16 13
 
< 0.1%
24 11
 
< 0.1%
25 11
 
< 0.1%
23 11
 
< 0.1%
Other values (21) 130
 
0.2%
(Missing) 67487
99.5%
ValueCountFrequency (%)
0 88
0.1%
1 2
 
< 0.1%
2 1
 
< 0.1%
3 4
 
< 0.1%
4 4
 
< 0.1%
5 7
 
< 0.1%
6 6
 
< 0.1%
7 8
 
< 0.1%
8 2
 
< 0.1%
9 6
 
< 0.1%
ValueCountFrequency (%)
30 2
 
< 0.1%
29 10
< 0.1%
28 13
< 0.1%
27 6
< 0.1%
26 10
< 0.1%
25 11
< 0.1%
24 11
< 0.1%
23 11
< 0.1%
22 10
< 0.1%
21 14
< 0.1%

hardship_loan_status
Categorical

High correlation  Missing 

Distinct4
Distinct (%)1.2%
Missing67487
Missing (%)99.5%
Memory size1.0 MiB
Late (16-30 days)
130 
Current
105 
In Grace Period
88 
Late (31-120 days)
 
11

Length

Max length18
Median length17
Mean length13.362275
Min length7

Characters and Unicode

Total characters4463
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIn Grace Period
2nd rowIn Grace Period
3rd rowIn Grace Period
4th rowCurrent
5th rowCurrent

Common Values

ValueCountFrequency (%)
Late (16-30 days) 130
 
0.2%
Current 105
 
0.2%
In Grace Period 88
 
0.1%
Late (31-120 days) 11
 
< 0.1%
(Missing) 67487
99.5%

Length

2026-01-19T10:07:51.472726image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:51.533899image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
late 141
17.8%
days 141
17.8%
16-30 130
16.4%
current 105
13.3%
in 88
11.1%
grace 88
11.1%
period 88
11.1%
31-120 11
 
1.4%

Most occurring characters

ValueCountFrequency (%)
458
 
10.3%
e 422
 
9.5%
r 386
 
8.6%
a 370
 
8.3%
t 246
 
5.5%
d 229
 
5.1%
n 193
 
4.3%
1 152
 
3.4%
( 141
 
3.2%
L 141
 
3.2%
Other values (16) 1725
38.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4463
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
458
 
10.3%
e 422
 
9.5%
r 386
 
8.6%
a 370
 
8.3%
t 246
 
5.5%
d 229
 
5.1%
n 193
 
4.3%
1 152
 
3.4%
( 141
 
3.2%
L 141
 
3.2%
Other values (16) 1725
38.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4463
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
458
 
10.3%
e 422
 
9.5%
r 386
 
8.6%
a 370
 
8.3%
t 246
 
5.5%
d 229
 
5.1%
n 193
 
4.3%
1 152
 
3.4%
( 141
 
3.2%
L 141
 
3.2%
Other values (16) 1725
38.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4463
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
458
 
10.3%
e 422
 
9.5%
r 386
 
8.6%
a 370
 
8.3%
t 246
 
5.5%
d 229
 
5.1%
n 193
 
4.3%
1 152
 
3.4%
( 141
 
3.2%
L 141
 
3.2%
Other values (16) 1725
38.7%

orig_projected_additional_accrued_interest
Real number (ℝ)

High correlation  Missing 

Distinct277
Distinct (%)99.6%
Missing67543
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean446.3523
Minimum11.19
Maximum2372.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:51.609540image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum11.19
5-th percentile52.05
Q1159.7275
median316.185
Q3578.475
95-th percentile1355.2815
Maximum2372.04
Range2360.85
Interquartile range (IQR)418.7475

Descriptive statistics

Standard deviation394.93211
Coefficient of variation (CV)0.88479909
Kurtosis2.6681953
Mean446.3523
Median Absolute Deviation (MAD)187.545
Skewness1.5704594
Sum124085.94
Variance155971.37
MonotonicityNot monotonic
2026-01-19T10:07:51.684712image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
242.34 2
 
< 0.1%
2372.04 1
 
< 0.1%
527.67 1
 
< 0.1%
138.39 1
 
< 0.1%
314.61 1
 
< 0.1%
888.96 1
 
< 0.1%
98.46 1
 
< 0.1%
304.65 1
 
< 0.1%
55.92 1
 
< 0.1%
381.06 1
 
< 0.1%
Other values (267) 267
 
0.4%
(Missing) 67543
99.6%
ValueCountFrequency (%)
11.19 1
< 0.1%
16.89 1
< 0.1%
29.37 1
< 0.1%
31.47 1
< 0.1%
34.71 1
< 0.1%
34.83 1
< 0.1%
35.28 1
< 0.1%
35.43 1
< 0.1%
36.87 1
< 0.1%
37.56 1
< 0.1%
ValueCountFrequency (%)
2372.04 1
< 0.1%
1899.63 1
< 0.1%
1649.04 1
< 0.1%
1516.53 1
< 0.1%
1511.22 1
< 0.1%
1472.13 1
< 0.1%
1462.68 1
< 0.1%
1462.2 1
< 0.1%
1429.71 1
< 0.1%
1407.42 1
< 0.1%

hardship_payoff_balance_amount
Real number (ℝ)

High correlation  Missing 

Distinct334
Distinct (%)100.0%
Missing67487
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean11576.675
Minimum568.17
Maximum38079.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:51.758829image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum568.17
5-th percentile1935.3205
Q15289.6875
median9657.01
Q316618.193
95-th percentile26422.693
Maximum38079.56
Range37511.39
Interquartile range (IQR)11328.505

Descriptive statistics

Standard deviation7777.3639
Coefficient of variation (CV)0.67181329
Kurtosis-0.02273092
Mean11576.675
Median Absolute Deviation (MAD)5040.9
Skewness0.82099342
Sum3866609.3
Variance60487389
MonotonicityNot monotonic
2026-01-19T10:07:51.841502image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13759.81 1
 
< 0.1%
5894.53 1
 
< 0.1%
4538.22 1
 
< 0.1%
7968.55 1
 
< 0.1%
18767.87 1
 
< 0.1%
10332.36 1
 
< 0.1%
13640.52 1
 
< 0.1%
9294.29 1
 
< 0.1%
8335.18 1
 
< 0.1%
6677.52 1
 
< 0.1%
Other values (324) 324
 
0.5%
(Missing) 67487
99.5%
ValueCountFrequency (%)
568.17 1
< 0.1%
683.67 1
< 0.1%
996.55 1
< 0.1%
1033.53 1
< 0.1%
1162.26 1
< 0.1%
1169.87 1
< 0.1%
1234.48 1
< 0.1%
1358.92 1
< 0.1%
1412.77 1
< 0.1%
1424.59 1
< 0.1%
ValueCountFrequency (%)
38079.56 1
< 0.1%
34631.14 1
< 0.1%
33348.82 1
< 0.1%
31708.61 1
< 0.1%
31670.2 1
< 0.1%
31399.44 1
< 0.1%
30682.55 1
< 0.1%
28146.83 1
< 0.1%
28058.41 1
< 0.1%
27695.36 1
< 0.1%

hardship_last_payment_amount
Real number (ℝ)

High correlation  Missing 

Distinct326
Distinct (%)97.6%
Missing67487
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean178.92257
Minimum0.01
Maximum1253.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:51.923663image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.313
Q135.1525
median119.47
Q3244.1975
95-th percentile563.439
Maximum1253.28
Range1253.27
Interquartile range (IQR)209.045

Descriptive statistics

Standard deviation192.97364
Coefficient of variation (CV)1.0785316
Kurtosis4.3936319
Mean178.92257
Median Absolute Deviation (MAD)99.755
Skewness1.8054536
Sum59760.14
Variance37238.827
MonotonicityNot monotonic
2026-01-19T10:07:52.007806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.32 2
 
< 0.1%
3.94 2
 
< 0.1%
0.3 2
 
< 0.1%
28.47 2
 
< 0.1%
0.01 2
 
< 0.1%
0.25 2
 
< 0.1%
0.03 2
 
< 0.1%
172.72 2
 
< 0.1%
71.66 1
 
< 0.1%
100.4 1
 
< 0.1%
Other values (316) 316
 
0.5%
(Missing) 67487
99.5%
ValueCountFrequency (%)
0.01 2
< 0.1%
0.02 1
< 0.1%
0.03 2
< 0.1%
0.06 1
< 0.1%
0.07 1
< 0.1%
0.08 1
< 0.1%
0.09 1
< 0.1%
0.1 1
< 0.1%
0.21 1
< 0.1%
0.22 1
< 0.1%
ValueCountFrequency (%)
1253.28 1
< 0.1%
992.33 1
< 0.1%
939.74 1
< 0.1%
836.05 1
< 0.1%
781.68 1
< 0.1%
740.38 1
< 0.1%
729.31 1
< 0.1%
722.14 1
< 0.1%
693.89 1
< 0.1%
662.56 1
< 0.1%

disbursement_method
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
Cash
65496 
DirectPay
 
2325

Length

Max length9
Median length4
Mean length4.1714071
Min length4

Characters and Unicode

Total characters282909
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCash
2nd rowCash
3rd rowCash
4th rowCash
5th rowCash

Common Values

ValueCountFrequency (%)
Cash 65496
96.6%
DirectPay 2325
 
3.4%

Length

2026-01-19T10:07:52.084460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:52.142600image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
cash 65496
96.6%
directpay 2325
 
3.4%

Most occurring characters

ValueCountFrequency (%)
a 67821
24.0%
C 65496
23.2%
s 65496
23.2%
h 65496
23.2%
D 2325
 
0.8%
i 2325
 
0.8%
r 2325
 
0.8%
e 2325
 
0.8%
c 2325
 
0.8%
t 2325
 
0.8%
Other values (2) 4650
 
1.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 282909
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 67821
24.0%
C 65496
23.2%
s 65496
23.2%
h 65496
23.2%
D 2325
 
0.8%
i 2325
 
0.8%
r 2325
 
0.8%
e 2325
 
0.8%
c 2325
 
0.8%
t 2325
 
0.8%
Other values (2) 4650
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 282909
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 67821
24.0%
C 65496
23.2%
s 65496
23.2%
h 65496
23.2%
D 2325
 
0.8%
i 2325
 
0.8%
r 2325
 
0.8%
e 2325
 
0.8%
c 2325
 
0.8%
t 2325
 
0.8%
Other values (2) 4650
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 282909
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 67821
24.0%
C 65496
23.2%
s 65496
23.2%
h 65496
23.2%
D 2325
 
0.8%
i 2325
 
0.8%
r 2325
 
0.8%
e 2325
 
0.8%
c 2325
 
0.8%
t 2325
 
0.8%
Other values (2) 4650
 
1.6%

debt_settlement_flag
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size596.1 KiB
False
66813 
True
 
1008
ValueCountFrequency (%)
False 66813
98.5%
True 1008
 
1.5%
2026-01-19T10:07:52.192689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Distinct49
Distinct (%)4.9%
Missing66813
Missing (%)98.5%
Memory size1.0 MiB
Minimum2013-10-01 00:00:00
Maximum2019-03-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:52.258752image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:52.343999image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

settlement_status
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.3%
Missing66813
Missing (%)98.5%
Memory size1.0 MiB
ACTIVE
440 
COMPLETE
429 
BROKEN
139 

Length

Max length8
Median length6
Mean length6.8511905
Min length6

Characters and Unicode

Total characters6906
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACTIVE
2nd rowCOMPLETE
3rd rowCOMPLETE
4th rowCOMPLETE
5th rowCOMPLETE

Common Values

ValueCountFrequency (%)
ACTIVE 440
 
0.6%
COMPLETE 429
 
0.6%
BROKEN 139
 
0.2%
(Missing) 66813
98.5%

Length

2026-01-19T10:07:52.431191image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:52.492325image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
active 440
43.7%
complete 429
42.6%
broken 139
 
13.8%

Most occurring characters

ValueCountFrequency (%)
E 1437
20.8%
C 869
12.6%
T 869
12.6%
O 568
 
8.2%
I 440
 
6.4%
A 440
 
6.4%
V 440
 
6.4%
M 429
 
6.2%
P 429
 
6.2%
L 429
 
6.2%
Other values (4) 556
 
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6906
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 1437
20.8%
C 869
12.6%
T 869
12.6%
O 568
 
8.2%
I 440
 
6.4%
A 440
 
6.4%
V 440
 
6.4%
M 429
 
6.2%
P 429
 
6.2%
L 429
 
6.2%
Other values (4) 556
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6906
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 1437
20.8%
C 869
12.6%
T 869
12.6%
O 568
 
8.2%
I 440
 
6.4%
A 440
 
6.4%
V 440
 
6.4%
M 429
 
6.2%
P 429
 
6.2%
L 429
 
6.2%
Other values (4) 556
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6906
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 1437
20.8%
C 869
12.6%
T 869
12.6%
O 568
 
8.2%
I 440
 
6.4%
A 440
 
6.4%
V 440
 
6.4%
M 429
 
6.2%
P 429
 
6.2%
L 429
 
6.2%
Other values (4) 556
 
8.1%

settlement_date
Date

Missing 

Distinct60
Distinct (%)6.0%
Missing66813
Missing (%)98.5%
Memory size1.0 MiB
Minimum2012-05-01 00:00:00
Maximum2019-03-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-19T10:07:52.571674image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2026-01-19T10:07:52.656318image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

settlement_amount
Real number (ℝ)

High correlation  Missing 

Distinct969
Distinct (%)96.1%
Missing66813
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean5003.1056
Minimum221.26
Maximum21676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:52.734055image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum221.26
5-th percentile788.528
Q12148.725
median4082.875
Q36960.75
95-th percentile12437.65
Maximum21676
Range21454.74
Interquartile range (IQR)4812.025

Descriptive statistics

Standard deviation3668.6096
Coefficient of variation (CV)0.73326648
Kurtosis1.1434313
Mean5003.1056
Median Absolute Deviation (MAD)2243.625
Skewness1.1441586
Sum5043130.5
Variance13458697
MonotonicityNot monotonic
2026-01-19T10:07:52.811251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7000 4
 
< 0.1%
8000 3
 
< 0.1%
1550 3
 
< 0.1%
4946 3
 
< 0.1%
7500 3
 
< 0.1%
1600 3
 
< 0.1%
3597 2
 
< 0.1%
839 2
 
< 0.1%
2982 2
 
< 0.1%
1968 2
 
< 0.1%
Other values (959) 981
 
1.4%
(Missing) 66813
98.5%
ValueCountFrequency (%)
221.26 1
< 0.1%
234 1
< 0.1%
250 1
< 0.1%
251 1
< 0.1%
268 1
< 0.1%
280 1
< 0.1%
293 1
< 0.1%
321 1
< 0.1%
325.03 1
< 0.1%
338.96 1
< 0.1%
ValueCountFrequency (%)
21676 1
< 0.1%
19892.11 1
< 0.1%
18906 1
< 0.1%
18410.76 1
< 0.1%
16807 1
< 0.1%
16376.05 1
< 0.1%
16302.44 1
< 0.1%
16078.46 1
< 0.1%
15880.69 1
< 0.1%
15773 1
< 0.1%

settlement_percentage
Real number (ℝ)

High correlation  Missing 

Distinct147
Distinct (%)14.6%
Missing66813
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean47.720089
Minimum0.45
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:52.894367image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.45
5-th percentile40
Q145
median45
Q350
95-th percentile60.0265
Maximum100
Range99.55
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.4371838
Coefficient of variation (CV)0.15585017
Kurtosis9.2196297
Mean47.720089
Median Absolute Deviation (MAD)4.275
Skewness1.4426776
Sum48101.85
Variance55.311703
MonotonicityNot monotonic
2026-01-19T10:07:52.995006image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 350
 
0.5%
50 162
 
0.2%
40 65
 
0.1%
45.01 54
 
0.1%
50.01 33
 
< 0.1%
55 33
 
< 0.1%
60 27
 
< 0.1%
44.99 23
 
< 0.1%
65 22
 
< 0.1%
49.99 20
 
< 0.1%
Other values (137) 219
 
0.3%
(Missing) 66813
98.5%
ValueCountFrequency (%)
0.45 1
 
< 0.1%
20 1
 
< 0.1%
22.23 1
 
< 0.1%
24.03 1
 
< 0.1%
28.5 1
 
< 0.1%
29.21 1
 
< 0.1%
29.59 1
 
< 0.1%
29.98 1
 
< 0.1%
30 6
< 0.1%
30.21 1
 
< 0.1%
ValueCountFrequency (%)
100 1
< 0.1%
92.44 1
< 0.1%
90 2
< 0.1%
84.07 1
< 0.1%
83.44 1
< 0.1%
81.69 1
< 0.1%
80 1
< 0.1%
74.89 1
< 0.1%
71 1
< 0.1%
70.96 1
< 0.1%

settlement_term
Real number (ℝ)

High correlation  Missing 

Distinct27
Distinct (%)2.7%
Missing66813
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean13.203373
Minimum0
Maximum30
Zeros77
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2026-01-19T10:07:53.068109image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q318
95-th percentile24
Maximum30
Range30
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.0986537
Coefficient of variation (CV)0.61337763
Kurtosis-1.1677485
Mean13.203373
Median Absolute Deviation (MAD)6
Skewness-0.23045822
Sum13309
Variance65.588191
MonotonicityNot monotonic
2026-01-19T10:07:53.136744image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
18 211
 
0.3%
24 194
 
0.3%
12 132
 
0.2%
1 89
 
0.1%
0 77
 
0.1%
6 71
 
0.1%
16 45
 
0.1%
8 34
 
0.1%
10 30
 
< 0.1%
14 25
 
< 0.1%
Other values (17) 100
 
0.1%
(Missing) 66813
98.5%
ValueCountFrequency (%)
0 77
0.1%
1 89
0.1%
2 7
 
< 0.1%
3 12
 
< 0.1%
4 18
 
< 0.1%
5 6
 
< 0.1%
6 71
0.1%
7 4
 
< 0.1%
8 34
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
28 1
 
< 0.1%
24 194
0.3%
23 6
 
< 0.1%
22 5
 
< 0.1%
21 1
 
< 0.1%
20 10
 
< 0.1%
19 2
 
< 0.1%
18 211
0.3%
17 3
 
< 0.1%

default_flag
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.0 MiB
0
59081 
1
8740 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters67821
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 59081
87.1%
1 8740
 
12.9%

Length

2026-01-19T10:07:53.208422image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-19T10:07:53.265528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
0 59081
87.1%
1 8740
 
12.9%

Most occurring characters

ValueCountFrequency (%)
0 59081
87.1%
1 8740
 
12.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 59081
87.1%
1 8740
 
12.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 59081
87.1%
1 8740
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 67821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 59081
87.1%
1 8740
 
12.9%

Correlations

2026-01-19T10:07:53.546053image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
acc_now_delinqacc_open_past_24mthsaddr_stateall_utilannual_incannual_inc_jointapplication_typeavg_cur_balbc_open_to_buybc_utilchargeoff_within_12_mthscollection_recovery_feecollections_12_mths_ex_meddebt_settlement_flagdefault_flagdelinq_2yrsdelinq_amntdisbursement_methoddtidti_jointemp_lengthfico_range_highfico_range_lowfunded_amntfunded_amnt_invgradehardship_amounthardship_dpdhardship_flaghardship_last_payment_amounthardship_loan_statushardship_payoff_balance_amounthardship_reasonhardship_statushome_ownershipidil_utilinitial_list_statusinq_fiinq_last_12minq_last_6mthsinstallmentint_ratelast_fico_range_highlast_fico_range_lowlast_pymnt_amntloan_amntloan_statusmax_bal_bcmo_sin_old_il_acctmo_sin_old_rev_tl_opmo_sin_rcnt_rev_tl_opmo_sin_rcnt_tlmort_accmths_since_last_delinqmths_since_last_major_derogmths_since_last_recordmths_since_rcnt_ilmths_since_recent_bcmths_since_recent_bc_dlqmths_since_recent_inqmths_since_recent_revol_delinqnum_accts_ever_120_pdnum_actv_bc_tlnum_actv_rev_tlnum_bc_satsnum_bc_tlnum_il_tlnum_op_rev_tlnum_rev_acctsnum_rev_tl_bal_gt_0num_satsnum_tl_120dpd_2mnum_tl_30dpdnum_tl_90g_dpd_24mnum_tl_op_past_12mopen_accopen_acc_6mopen_act_ilopen_il_12mopen_il_24mopen_rv_12mopen_rv_24morig_projected_additional_accrued_interestout_prncpout_prncp_invpct_tl_nvr_dlqpercent_bc_gt_75pub_recpub_rec_bankruptciespurposepymnt_planrecoveriesrevol_balrevol_bal_jointrevol_utilsec_app_chargeoff_within_12_mthssec_app_collections_12_mths_ex_medsec_app_fico_range_highsec_app_fico_range_lowsec_app_inq_last_6mthssec_app_mort_accsec_app_mths_since_last_major_derogsec_app_num_rev_acctssec_app_open_accsec_app_open_act_ilsec_app_revol_utilsettlement_amountsettlement_percentagesettlement_statussettlement_termsub_gradetax_lienstermtot_coll_amttot_cur_baltot_hi_cred_limtotal_acctotal_bal_ex_morttotal_bal_iltotal_bc_limittotal_cu_tltotal_il_high_credit_limittotal_pymnttotal_pymnt_invtotal_rec_inttotal_rec_late_feetotal_rec_prncptotal_rev_hi_limverification_statusverification_status_joint
acc_now_delinq1.000-0.0050.000-0.0180.016-0.0030.0070.0180.006-0.0180.0480.0090.0100.0000.0000.1280.7590.0070.0090.0230.004-0.043-0.0430.0010.0010.011NaNNaN0.000NaN1.000NaN1.0001.0000.005-0.020-0.0170.012-0.0030.006-0.0030.0010.023-0.015-0.015-0.0000.0010.000-0.0040.0160.0310.0000.0010.027-0.144-0.099-0.0080.0070.008-0.1030.002-0.1290.029-0.0090.003-0.0080.0150.0140.0110.0240.0020.0070.3480.8930.088-0.0030.017-0.0050.014-0.007-0.006-0.005-0.004NaN-0.019-0.019-0.059-0.014-0.004-0.0100.0000.0000.008-0.004-0.002-0.017-0.005-0.008-0.005-0.0050.0110.0280.0290.012-0.005-0.022-0.0450.0110.0870.028-0.0400.0180.0030.004-0.0010.0210.0240.0280.0120.008-0.0010.0060.0170.0170.0170.0200.0110.0140.0050.0120.000
acc_open_past_24mths-0.0051.0000.018-0.0280.1170.1070.034-0.0050.142-0.1780.0030.0810.0190.0290.089-0.047-0.0050.0110.1510.1240.008-0.107-0.107-0.005-0.0050.0680.128-0.0690.0000.0570.0000.0370.0760.0000.0350.0020.2500.0110.3190.4310.2770.0100.166-0.150-0.1500.062-0.0050.042-0.0980.005-0.056-0.520-0.5300.0940.1230.133-0.098-0.442-0.4770.163-0.1950.1250.0780.2020.3130.2740.2640.2730.4200.3560.3090.4670.0000.000-0.0350.7450.4680.5320.2560.4260.5740.6070.8100.119-0.067-0.067-0.004-0.1480.1210.1130.0200.0000.080-0.0030.059-0.2230.0060.017-0.048-0.0480.1270.0800.0720.1170.1420.076-0.1550.0360.0060.0440.0420.0590.0270.0180.0760.1660.1760.4040.2200.2880.0520.1550.2400.0030.0030.0110.017-0.0140.1430.0690.024
addr_state0.0000.0181.0000.0120.0250.0700.0500.0340.0320.0240.0000.0000.0170.0400.0390.0000.0000.0270.0240.0470.0190.0110.0110.0230.0220.0170.0490.2200.0190.3110.2710.0750.2430.0000.1101.0000.0140.0370.0470.0400.0260.0210.0110.0220.0230.0130.0230.0250.0000.0380.0170.0140.0000.0320.0000.0200.0530.0000.0000.0100.0310.0000.0000.0280.0210.0240.0250.0400.0270.0210.0210.0250.0190.0000.0000.0130.0250.0050.0160.0200.0320.0130.0140.0000.0170.0170.0130.0240.0200.0430.0210.0220.0000.0230.0000.0170.0000.0560.0380.0380.0000.0430.0000.0640.0810.0630.0430.0000.0920.1230.0880.0100.0140.0500.0000.0550.0320.0310.0240.0170.0210.0550.0200.0170.0170.0130.0010.0160.0260.0180.000
all_util-0.018-0.0280.0121.0000.0570.0250.0300.234-0.5320.6060.0030.070-0.0180.0210.0680.012-0.0160.0320.2030.1800.026-0.385-0.3850.0090.0090.1320.0760.0590.0000.0800.000-0.0150.1600.1560.038-0.1200.5540.0490.0800.026-0.0400.0340.319-0.254-0.2540.0200.0090.0300.1570.060-0.0620.1450.0400.0080.020-0.006-0.047-0.1930.1600.0340.0320.0460.065-0.035-0.015-0.214-0.2160.234-0.246-0.223-0.010-0.0400.0000.0000.014-0.025-0.039-0.0370.3080.1950.218-0.155-0.1710.083-0.047-0.047-0.0740.512-0.011-0.0210.0450.0000.0700.1870.1140.672-0.018-0.019-0.159-0.159-0.0180.0670.051-0.0620.0190.1040.3550.104-0.0310.0930.0510.1130.0090.068-0.0120.1940.044-0.0080.3850.357-0.2760.0620.2560.0630.0630.1640.0500.017-0.2890.1100.044
annual_inc0.0160.1170.0250.0571.0000.6730.0000.4520.2130.0240.013-0.037-0.0090.0000.0000.0900.0130.000-0.199-0.0940.0000.0810.0810.4630.4620.0030.405-0.0140.0000.2041.0000.5141.0001.0000.0060.037-0.0640.0090.1200.1320.0430.440-0.1340.0840.0840.2580.4630.0000.3780.2170.2380.015-0.0620.359-0.070-0.022-0.061-0.1530.006-0.068-0.062-0.0580.0440.1980.1550.2220.2490.2570.1650.2120.1540.2680.0000.0000.0310.0910.2710.0750.2560.1470.2110.001-0.0000.3880.0920.092-0.0600.010-0.032-0.0640.0000.000-0.0420.4140.3240.086-0.017-0.0260.1210.121-0.0100.1260.0590.1660.1750.067-0.0090.407-0.0310.0000.1440.0000.0560.000-0.0390.5270.5580.3320.5000.3710.3850.1110.4150.3240.3240.242-0.0000.3020.4130.0220.000
annual_inc_joint-0.0030.1070.0700.0250.6731.0001.0000.3850.1800.0460.026-0.059-0.0080.0000.0080.110-0.0020.028-0.103-0.1530.0390.0540.0540.4020.4020.0590.030-0.0300.0650.0590.0000.4630.2850.4020.1180.064-0.0840.0710.0800.0750.0400.362-0.1660.0640.0640.2540.4020.0000.3040.1990.2300.006-0.0550.323-0.104-0.124-0.045-0.0990.030-0.092-0.041-0.0770.0530.1660.1510.1860.2130.2480.1700.2120.1510.2730.0000.0000.0740.0720.2730.0700.2250.1010.140-0.010-0.0040.0530.2490.249-0.1000.032-0.095-0.1080.0500.000-0.0590.3440.4910.090-0.028-0.0400.1600.1600.0250.3010.0540.2840.3310.2430.0230.154-0.4220.173-0.0540.0480.0050.063-0.0380.4910.5230.3300.4220.3090.3240.1080.3640.1880.1880.148-0.0150.1860.3540.0540.045
application_type0.0070.0340.0500.0300.0001.0001.0000.0320.0190.0460.0000.0000.0040.0190.0390.0000.0000.0060.1521.0000.0970.1120.1120.1370.1370.0060.2390.1130.0090.2090.0300.2450.0940.1490.0811.0000.0000.0910.0140.0070.0380.1020.0550.0720.0720.0770.1370.1860.0000.0040.0300.0350.0250.0070.0000.0160.0750.0150.0370.0350.0150.0330.0130.0530.0510.0390.0650.0000.0350.0440.0490.0190.0000.0050.0000.0260.0170.0230.0000.0020.0000.0450.0540.2410.2520.2520.0180.0460.0090.0030.0320.0070.0000.0001.0000.0461.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.1840.0000.0730.0630.0330.0000.0670.0000.0220.0000.0280.0080.0140.0120.0370.0300.0810.0810.0280.0060.1090.0000.0561.000
avg_cur_bal0.018-0.0050.0340.2340.4520.3850.0321.0000.0220.1290.013-0.042-0.0160.0070.0390.0730.0160.0000.045-0.0120.0100.1250.1250.2700.2700.0210.2520.0800.0000.1300.0000.3260.0470.0000.079-0.0070.0740.0230.1350.105-0.0260.237-0.0870.1080.1080.1750.2700.0140.2940.2010.1770.1310.0000.640-0.072-0.0290.030-0.1450.132-0.043-0.011-0.0330.021-0.082-0.115-0.099-0.0120.249-0.162-0.035-0.1150.0120.0000.0000.0200.0050.0120.0160.2010.1420.183-0.148-0.2000.2440.0400.040-0.0530.109-0.089-0.0990.0210.000-0.0430.2830.2350.193-0.052-0.0650.2200.220-0.0530.4670.1350.0800.1140.1160.0490.267-0.0240.0000.0580.016-0.0020.025-0.0500.9260.8760.1930.4800.4070.1640.1690.3970.2020.2020.147-0.0040.1890.1860.0210.000
bc_open_to_buy0.0060.1420.032-0.5320.2130.1800.0190.0221.000-0.746-0.014-0.081-0.0100.0150.046-0.0700.0080.023-0.053-0.0260.0070.4940.4940.2160.2160.0870.121-0.0160.0000.0360.0000.2270.0320.0000.0250.179-0.0510.0470.0270.0510.0170.178-0.3720.3130.3130.0910.2160.0220.2040.0280.157-0.127-0.1070.1020.0150.0530.019-0.041-0.241-0.037-0.032-0.023-0.1090.2990.1300.5360.4270.0130.3740.3170.1340.3190.0000.000-0.0670.1270.3170.130-0.0040.0330.0350.1510.1750.1100.1430.1430.171-0.637-0.087-0.0800.0150.000-0.0840.1960.218-0.610-0.029-0.0230.3140.3140.0130.0450.0450.1960.149-0.015-0.4230.1480.0430.0000.0100.088-0.0210.005-0.0430.1370.2590.2320.1300.0450.776-0.0120.0640.0630.063-0.056-0.0620.0880.6790.0320.000
bc_util-0.018-0.1780.0240.6060.0240.0460.0460.129-0.7461.000-0.0090.061-0.0360.0280.0660.013-0.0160.0510.1800.1650.013-0.438-0.4380.0530.0530.1300.0550.0670.0000.0370.0000.0240.0000.1270.019-0.191-0.0610.092-0.083-0.119-0.0740.0800.306-0.226-0.2260.0230.0530.0400.3860.0590.0170.1690.1670.0270.001-0.0030.0430.1000.2260.0190.0910.018-0.0080.0670.131-0.196-0.1610.020-0.148-0.1230.132-0.1010.0000.0140.004-0.185-0.101-0.1820.057-0.090-0.067-0.175-0.1850.030-0.083-0.083-0.0360.863-0.027-0.0310.0680.0000.0650.3400.2060.8630.001-0.050-0.171-0.171-0.0730.0960.025-0.0460.0150.0420.4780.063-0.0390.0370.0600.119-0.0020.050-0.0690.078-0.019-0.0710.1300.030-0.2590.0020.0260.1290.1290.2300.0370.086-0.2270.0980.040
chargeoff_within_12_mths0.0480.0030.0000.0030.0130.0260.0000.013-0.014-0.0091.0000.0020.0580.0200.0000.1420.0080.000-0.000-0.0000.000-0.071-0.071-0.009-0.0090.0090.021-0.0550.000-0.0600.085-0.0030.0450.0000.000-0.0040.0080.0020.0080.0120.007-0.0070.018-0.027-0.0270.004-0.0090.000-0.0250.0200.034-0.000-0.0050.033-0.118-0.211-0.029-0.0140.003-0.049-0.004-0.0560.144-0.016-0.002-0.0110.0290.0270.0020.041-0.0040.0050.0560.0000.2720.0050.0060.0170.0040.0140.0090.0020.0040.027-0.008-0.008-0.096-0.010-0.012-0.0160.0000.0000.001-0.022-0.023-0.0090.2010.001-0.059-0.0590.0150.000-0.0700.003-0.021-0.0040.015-0.030-0.0270.0000.0260.000-0.0040.0000.0030.0140.0130.0480.0010.007-0.0300.0160.010-0.001-0.0010.0020.012-0.001-0.0210.0150.000
collection_recovery_fee0.0090.0810.0000.070-0.037-0.0590.000-0.042-0.0810.0610.0021.0000.0100.3630.3280.0220.0110.0160.0500.0200.003-0.108-0.1080.0360.0350.0530.0680.1870.0000.0850.0000.0810.3190.0840.000-0.1620.0530.0180.0270.0570.0690.0400.169-0.404-0.404-0.1570.0360.124-0.022-0.012-0.034-0.055-0.058-0.033-0.010-0.013-0.054-0.045-0.053-0.011-0.056-0.0080.0200.0220.0440.0070.0180.0200.0230.0230.0420.0230.0000.0000.0170.0720.0210.0470.0230.0450.0480.0540.0680.092-0.230-0.230-0.0220.0660.0250.0150.0090.0000.979-0.010-0.0210.0600.0100.045-0.092-0.0920.104-0.040-0.024-0.008-0.006-0.0010.0350.355-0.0510.255-0.1440.0520.0200.0970.015-0.033-0.0480.0200.0090.024-0.0670.0130.004-0.082-0.0830.0460.154-0.210-0.0570.0410.020
collections_12_mths_ex_med0.0100.0190.017-0.018-0.009-0.0080.004-0.016-0.010-0.0360.0580.0101.0000.0000.0100.081-0.0000.007-0.012-0.0370.007-0.092-0.092-0.026-0.0260.013-0.0460.0070.000-0.0330.000-0.0560.2930.0900.0000.0210.0070.0040.0080.0180.010-0.0230.023-0.048-0.048-0.023-0.0260.000-0.0610.009-0.013-0.017-0.014-0.017-0.048-0.143-0.0310.000-0.013-0.014-0.010-0.0160.068-0.013-0.001-0.006-0.0120.0100.004-0.000-0.0040.0090.0000.0000.1430.0150.0110.0130.0060.001-0.0020.0150.018-0.0440.0070.007-0.063-0.0340.008-0.0060.0030.0040.008-0.051-0.055-0.0390.0180.085-0.076-0.076-0.025-0.034-0.007-0.028-0.006-0.011-0.0030.062-0.0400.0370.0510.0160.0130.0140.226-0.012-0.0120.007-0.018-0.000-0.045-0.0040.003-0.026-0.026-0.0090.007-0.028-0.0390.0110.014
debt_settlement_flag0.0000.0290.0400.0210.0000.0000.0190.0070.0150.0280.0200.3630.0001.0000.3190.0000.0050.0160.0000.0000.0100.0400.0400.0160.0160.0600.0000.0000.0000.0000.1280.0000.0820.0600.0141.0000.0080.0280.0130.0090.0000.0100.0510.1870.1870.0690.0160.3250.0000.0000.0050.0090.0040.0040.0000.0000.0100.0020.0090.0000.0000.0000.0000.0120.0230.0000.0040.0040.0210.0200.0220.0140.0000.0060.0000.0200.0160.0020.0000.0000.0000.0220.0270.0000.0760.0760.0000.0300.0000.0130.0160.0000.3560.0000.0000.0290.0000.0860.0000.0000.0290.0000.0000.0000.0410.0000.0001.0001.0001.0001.0000.0660.0000.0240.0090.0130.0000.0170.0080.0000.0100.0000.0000.0270.0280.0390.0270.0540.0000.0270.031
default_flag0.0000.0890.0390.0680.0000.0080.0390.0390.0460.0660.0000.3280.0100.3191.0000.0110.0130.0540.0000.0000.0180.1200.1200.0510.0520.2280.0000.2860.0490.1370.2110.1580.2610.5040.0641.0000.0520.0610.0390.0510.0690.0400.2100.6720.6720.2160.0511.0000.0080.0180.0430.0400.0330.0240.0040.0190.0370.0240.0370.0220.0590.0090.0000.0240.0470.0000.0040.0040.0270.0130.0460.0210.0000.0000.0000.0720.0200.0540.0050.0460.0500.0590.0710.0000.2060.2060.0050.0770.0110.0290.0470.0480.3460.0000.0000.0630.0000.0950.1550.1550.1250.0320.0000.0000.0400.0000.0600.0000.0000.0000.0000.2340.0000.0920.0080.0370.0100.0110.0220.0160.0470.0030.0200.1510.1510.0460.0780.2560.0230.0890.000
delinq_2yrs0.128-0.0470.0000.0120.0900.1100.0000.073-0.0700.0130.1420.0220.0810.0000.0111.0000.1140.007-0.015-0.0490.006-0.219-0.2190.0040.0040.024-0.042-0.0070.0000.0290.244-0.0640.1010.0000.010-0.029-0.0310.0090.0140.0350.0210.0140.074-0.119-0.1190.0020.0040.000-0.0500.0860.1070.0140.0020.110-0.820-0.543-0.0670.0130.047-0.632-0.031-0.7210.202-0.0320.016-0.0320.0430.0840.0230.0930.0120.0600.0220.0520.511-0.0230.0630.0050.056-0.007-0.017-0.020-0.039-0.071-0.023-0.023-0.4860.012-0.043-0.0620.0090.0000.019-0.043-0.0580.0100.0800.039-0.142-0.142-0.0060.087-0.1290.007-0.0210.0060.029-0.0030.0450.000-0.0590.0200.0180.0060.0230.0880.0890.1290.0330.049-0.0890.0230.0680.0350.0350.0490.0510.026-0.0660.0130.000
delinq_amnt0.759-0.0050.000-0.0160.013-0.0020.0000.0160.008-0.0160.0080.011-0.0000.0050.0130.1141.0000.0000.0120.0090.002-0.037-0.037-0.001-0.0010.000NaNNaN0.000NaN1.000NaN1.0001.0000.000-0.010-0.0200.006-0.007-0.000-0.003-0.0000.016-0.016-0.016-0.002-0.0010.000-0.0030.0140.0230.0010.0000.020-0.124-0.0760.0010.0080.008-0.0810.001-0.1070.016-0.0060.004-0.0070.0090.0130.0100.0160.0030.0060.3570.0120.064-0.0050.017-0.0030.015-0.009-0.004-0.006-0.005NaN-0.013-0.013-0.050-0.013-0.003-0.0080.0000.0000.010-0.002-0.009-0.014-0.006-0.009-0.006-0.0060.0030.0150.0290.001-0.017-0.032-0.0280.0160.0750.000-0.0310.0000.0020.0070.0000.0200.0230.0200.0130.0090.0020.0060.0170.0100.0100.0130.0130.0070.0090.0081.000
disbursement_method0.0070.0110.0270.0320.0000.0280.0060.0000.0230.0510.0000.0160.0070.0160.0540.0070.0001.0000.0120.0240.0280.0290.0290.0940.0930.1540.0000.0570.0000.0000.0210.0000.0730.2450.0221.0000.0180.0850.0070.0130.0330.0440.1630.0740.0740.0820.0940.1940.0180.0210.0140.0000.0170.0130.0000.0150.0740.0370.0130.0190.0220.0000.0040.0400.0310.0270.0000.0130.0280.0000.0320.0220.0000.0050.0040.0120.0230.0090.0000.0190.0240.0000.0090.0000.2530.2530.0220.0360.0120.0110.1260.0000.0180.0270.0980.0480.0000.0000.0400.0400.0000.0430.0000.0430.0280.0000.0350.0000.1330.0000.0000.1930.0010.0160.0000.0230.0120.0050.0270.0150.0490.0220.0150.1730.1730.0910.0060.1730.0330.0321.000
dti0.0090.1510.0240.203-0.199-0.1030.1520.045-0.0530.180-0.0000.050-0.0120.0000.000-0.0150.0120.0121.0000.6070.009-0.014-0.0140.0570.0570.0020.1190.0690.0000.1410.0000.0770.0000.0940.0000.032-0.0400.0150.1020.036-0.0060.0620.188-0.063-0.063-0.0220.0560.0050.1720.0670.0630.004-0.061-0.0110.0090.0320.078-0.2200.0190.0090.021-0.002-0.0580.1730.2590.1170.0920.2970.1960.1570.2600.3190.0000.000-0.0260.0880.3230.0420.4250.1920.294-0.0110.0140.1130.0500.0500.0750.171-0.039-0.0230.0000.0000.0510.2700.2480.178-0.025-0.0160.0370.037-0.0290.1110.0730.0570.1060.1660.0720.1170.0231.0000.0360.000-0.0320.016-0.0290.1460.1430.2520.4490.4230.0880.1540.4580.0080.0090.1170.002-0.0320.1590.0100.047
dti_joint0.0230.1240.0470.180-0.094-0.1531.000-0.012-0.0260.165-0.0000.020-0.0370.0000.000-0.0490.0090.0240.6071.0000.007-0.037-0.0370.0600.0590.0960.4570.0610.0290.5170.3500.3560.2510.4990.0300.044-0.0170.0600.1130.0350.0150.0750.225-0.073-0.0730.0010.0590.0420.1570.0690.0460.014-0.060-0.0230.0700.1280.176-0.1950.0000.0720.0290.057-0.0570.1910.2500.1430.0900.2540.1840.1360.2510.2690.0000.000-0.0290.0580.2690.0540.3330.1780.259-0.0270.0060.4970.0900.0900.0710.165-0.010-0.0110.0610.0410.0200.2680.4460.176-0.016-0.0180.0430.0430.0310.0020.0660.2370.3550.3480.1270.3070.3170.0000.2670.083-0.0000.081-0.0140.0880.0950.2130.4050.3640.1040.1660.389-0.012-0.0120.1300.007-0.0660.1650.1350.171
emp_length0.0040.0080.0190.0260.0000.0390.0970.0100.0070.0130.0000.0030.0070.0100.0180.0060.0020.0280.0090.0071.0000.0120.0120.0320.0320.0090.0000.0360.0050.0570.0000.0530.0370.0800.0901.0000.0400.0370.0090.0100.0020.0280.0050.0150.0150.0170.0320.0170.0100.0520.0830.0090.0030.0420.0170.0180.0270.0090.0170.0180.0000.0140.0070.0290.0420.0260.0360.0180.0380.0450.0430.0200.0110.0040.0070.0110.0210.0080.0450.0160.0160.0080.0040.0030.0150.0150.0090.0160.0080.0120.0200.0070.0000.0050.0380.0150.0000.0160.0190.0190.0000.0240.0260.0120.0310.0380.0230.0000.0000.0000.0000.0110.0080.0600.0070.0150.0000.0400.0120.0170.0160.0300.0130.0290.0290.0240.0050.0280.0130.0390.041
fico_range_high-0.043-0.1070.011-0.3850.0810.0540.1120.1250.494-0.438-0.071-0.108-0.0920.0400.120-0.219-0.0370.029-0.014-0.0370.0121.0001.0000.1260.1260.2010.0390.0490.0000.0160.0000.1640.0000.0000.0450.111-0.1210.089-0.047-0.127-0.1080.074-0.4310.4270.4270.0420.1270.1100.0760.0240.1120.1070.0730.0890.1050.0880.2720.0000.0560.0060.0770.038-0.270-0.092-0.1780.0660.0360.0100.0130.007-0.1750.0540.0110.013-0.156-0.1040.042-0.0570.039-0.011-0.000-0.120-0.1430.0600.1130.1140.357-0.407-0.254-0.2280.0430.000-0.1070.0180.061-0.420-0.045-0.0450.4500.450-0.0540.034-0.0460.0590.0440.045-0.3070.0900.0270.0000.0110.183-0.0780.045-0.2460.1330.2230.0200.0670.0380.3730.0110.0920.0170.017-0.110-0.0600.0540.3610.1230.049
fico_range_low-0.043-0.1070.011-0.3850.0810.0540.1120.1250.494-0.438-0.071-0.108-0.0920.0400.120-0.219-0.0370.029-0.014-0.0370.0121.0001.0000.1260.1260.2010.0390.0490.0000.0160.0000.1640.0000.0000.0450.111-0.1210.089-0.047-0.127-0.1080.074-0.4310.4270.4270.0420.1270.1100.0760.0240.1120.1070.0730.0890.1050.0880.2720.0000.0560.0060.0770.038-0.270-0.092-0.1780.0660.0360.0100.0130.007-0.1750.0540.0110.013-0.156-0.1040.042-0.0570.039-0.011-0.000-0.120-0.1430.0600.1130.1140.357-0.407-0.254-0.2280.0430.000-0.1070.0180.061-0.420-0.045-0.0450.4500.450-0.0540.034-0.0460.0590.0440.045-0.3070.0900.0270.0000.0110.183-0.0780.045-0.2460.1330.2230.0200.0670.0380.3730.0110.0920.0170.017-0.110-0.0600.0540.3610.1230.049
funded_amnt0.001-0.0050.0230.0090.4630.4020.1370.2700.2160.053-0.0090.036-0.0260.0160.0510.004-0.0010.0940.0570.0600.0320.1260.1261.0000.9990.0710.7950.0620.0040.3790.0000.8820.0000.0000.0810.023-0.0980.113-0.0020.004-0.0350.9640.0900.1020.1020.4621.0000.0490.3990.1370.1860.0520.0320.225-0.0200.0190.0270.0130.036-0.0450.009-0.033-0.0590.1990.1600.2190.2120.1200.1780.1880.1590.2010.0000.006-0.030-0.0350.204-0.0280.088-0.0130.023-0.044-0.0320.7860.2190.2190.0640.038-0.075-0.0850.0950.0000.0340.4570.4180.114-0.066-0.0860.2330.233-0.0860.2140.1250.2380.2400.0870.0090.823-0.0620.1360.3250.0620.0130.440-0.0800.3240.3540.2210.3380.1740.3980.0720.2170.6610.6610.7010.0040.5470.4180.1550.173
funded_amnt_inv0.001-0.0050.0220.0090.4620.4020.1370.2700.2160.053-0.0090.035-0.0260.0160.0520.004-0.0010.0930.0570.0590.0320.1260.1260.9991.0000.0710.7940.0630.0040.3770.0000.8820.0000.0250.0810.027-0.0980.112-0.0020.004-0.0360.9630.0900.1030.1030.4610.9990.0510.3990.1370.1860.0520.0320.225-0.0200.0190.0320.0130.035-0.0450.009-0.033-0.0590.1990.1600.2190.2120.1200.1780.1880.1590.2010.0000.007-0.030-0.0350.204-0.0280.088-0.0130.023-0.044-0.0320.7850.2210.2210.0650.038-0.074-0.0840.0970.0000.0330.4560.4180.114-0.066-0.0860.2320.232-0.0860.2140.1240.2380.2400.0870.0090.823-0.0630.1420.3260.0630.0130.438-0.0800.3240.3540.2210.3380.1740.3980.0720.2170.6590.6610.7000.0040.5450.4190.1560.170
grade0.0110.0680.0170.1320.0030.0590.0060.0210.0870.1300.0090.0530.0130.0600.2280.0240.0000.1540.0020.0960.0090.2010.2010.0710.0711.0000.2800.0000.0010.1610.0000.1070.0000.0630.0371.0000.0610.1400.0450.0550.0720.0700.6860.1720.1720.0500.0710.1000.0000.0220.0540.0300.0310.0210.0270.0230.0470.0210.0210.0170.0650.0250.0200.0040.0320.0290.0370.0080.0140.0230.0330.0170.0130.0110.0140.0670.0160.0540.0090.0550.0580.0480.0480.2830.0340.0340.0460.1290.0070.0320.0770.0000.0590.0100.0000.1250.0680.0400.1840.1840.0440.0390.0340.0360.0000.0000.1340.1450.0000.0520.0791.0000.0040.3800.0000.0250.0120.0240.0050.0100.0770.0120.0090.0760.0760.1960.0210.0490.0380.1780.091
hardship_amountNaN0.1280.0490.0760.4050.0300.2390.2520.1210.0550.0210.068-0.0460.0000.000-0.042NaN0.0000.1190.4570.0000.0390.0390.7950.7940.2801.0000.0030.1840.4450.0000.9260.0000.1310.0660.250-0.0220.0000.1930.1640.0610.7660.571-0.000-0.0000.4940.7950.0690.2680.0750.0790.0710.0000.150-0.0140.0890.195-0.1300.0590.043-0.1500.073-0.1060.0600.0760.1090.0440.0450.1350.0540.0810.1651.0001.000-0.0830.1020.1610.0610.1510.1310.178-0.0460.0231.0000.3050.3050.0460.099-0.0210.0080.0000.0820.0700.2590.3360.051-0.378NaN-0.372-0.372-0.1820.3780.5000.3450.2060.1480.2090.902-0.1760.3400.7350.314-0.0140.413-0.0270.2870.3140.0470.3040.2520.254-0.0320.2710.5250.5250.7820.0430.2410.2730.0990.245
hardship_dpdNaN-0.0690.2200.059-0.014-0.0300.1130.080-0.0160.067-0.0550.1870.0070.0000.286-0.007NaN0.0570.0690.0610.0360.0490.0490.0620.0630.0000.0031.0000.2450.2140.7760.0150.2470.2300.0000.009-0.0480.000-0.0650.0430.0030.054-0.014-0.203-0.203-0.0890.0620.1410.0490.083-0.0100.1010.053-0.071-0.0420.082-0.114-0.0700.051-0.198-0.053-0.116-0.1000.011-0.059-0.027-0.0870.022-0.120-0.149-0.065-0.1101.0001.000-0.065-0.072-0.106-0.0860.0540.0230.064-0.135-0.136-0.010-0.004-0.0040.0360.0790.0500.0480.0480.2650.186-0.0050.1250.1040.172NaN0.2110.2110.000-0.208-0.300-0.251-0.307-0.076-0.1720.402-0.4720.4280.1760.0000.0390.000-0.0820.0220.011-0.0980.0710.0810.014-0.0430.087-0.047-0.0470.0310.486-0.107-0.0540.0000.000
hardship_flag0.0000.0000.0190.0000.0000.0650.0090.0000.0000.0000.0000.0000.0000.0000.0490.0000.0000.0000.0000.0290.0050.0000.0000.0040.0040.0010.1840.2451.0000.0480.0520.0000.1900.9980.0031.0000.0000.0000.0000.0000.0000.0200.0150.0180.0180.0000.0040.2060.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0030.0050.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0060.0000.0000.0000.0110.0110.0000.0000.2210.0280.0280.0050.0080.0000.0000.0260.9060.0000.0000.0410.0000.0000.0000.0070.0070.0830.0001.0000.0000.0000.0220.0001.0001.0001.0001.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0310.0080.0000.0000.000
hardship_last_payment_amountNaN0.0570.3110.0800.2040.0590.2090.1300.0360.037-0.0600.085-0.0330.0000.1370.029NaN0.0000.1410.5170.0570.0160.0160.3790.3770.1610.4450.2140.0481.0000.0900.4050.0860.0680.0700.047-0.0020.147-0.0060.1090.0570.3290.246-0.120-0.1200.2020.3790.0000.0550.0800.0460.0670.034-0.001-0.0190.1020.088-0.0660.0830.001-0.096-0.029-0.023-0.0100.0040.0610.0240.1220.0660.0500.0060.0881.0001.000-0.0650.0440.0860.0430.1840.0550.1370.0300.0130.4300.1160.116-0.0200.0440.0610.0720.0000.0000.0860.1310.2530.044-0.172NaN-0.247-0.247-0.005-0.115-0.5000.3670.0440.1620.0460.140-0.0500.1640.2370.1420.0610.336-0.0620.1360.1390.0900.2640.2960.0960.0660.2700.2630.2630.3940.1510.1590.1190.0420.000
hardship_loan_status1.0000.0000.2710.0001.0000.0000.0300.0000.0000.0000.0850.0000.0000.1280.2110.2441.0000.0210.0000.3500.0000.0000.0000.0000.0000.0000.0000.7760.0520.0901.0000.0000.3840.1320.0001.0000.0000.0000.0000.0710.0000.0000.0000.1280.1190.0710.0000.1350.0000.0730.1400.0000.0450.1060.0000.0000.0000.0000.1580.1050.0000.0000.0000.0800.0420.0000.0000.0000.0000.0580.0630.0001.0001.0000.2090.0000.0000.0720.0000.0000.0000.0000.0000.0000.0000.0000.0680.0000.0000.0000.0000.0570.0000.0000.0000.0530.0001.0000.4700.4700.0000.1510.0000.4100.4470.1400.0000.0000.0000.0000.0000.0000.0420.0001.0000.1201.0000.0000.0000.0000.0000.1790.0000.0440.0440.0000.1400.0000.0000.0000.267
hardship_payoff_balance_amountNaN0.0370.075-0.0150.5140.4630.2450.3260.2270.024-0.0030.081-0.0560.0000.158-0.064NaN0.0000.0770.3560.0530.1640.1640.8820.8820.1070.9260.0150.0000.4050.0001.0000.0000.0000.1140.319-0.0980.0800.0900.112-0.0180.8400.2470.0620.0620.4830.8820.1150.3590.0930.1540.0950.0410.2190.0050.0550.162-0.0490.0890.101-0.1080.108-0.1500.1200.0960.1700.1030.0220.1540.0940.0910.1631.0001.000-0.0880.0270.162-0.0190.0820.0370.070-0.091-0.0420.9260.3310.3300.0810.045-0.014-0.0210.0000.0000.0830.3270.5600.036-0.447NaN0.1450.1450.1840.6170.5000.6730.4300.1620.0460.972-0.2120.0000.6250.0500.0130.354-0.0580.3490.3930.0580.3320.2270.382-0.0570.2710.5250.5250.6570.0790.3070.3820.1580.311
hardship_reason1.0000.0760.2430.1601.0000.2850.0940.0470.0320.0000.0450.3190.2930.0820.2610.1011.0000.0730.0000.2510.0370.0000.0000.0000.0000.0000.0000.2470.1900.0860.3840.0001.0000.1990.1061.0000.0000.0340.0000.0950.0780.0280.0000.1360.1260.0000.0000.1590.0000.0000.0000.0000.0000.0000.0000.0810.0000.0000.1550.0440.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.2500.0920.0000.1630.0000.0000.0000.1760.1710.0150.0000.0000.0000.0860.1250.0000.0970.1570.3190.0000.4680.0000.0001.0000.2730.2730.0000.3790.0000.1720.4470.7260.0000.4700.0000.0000.0000.0000.2020.0001.0000.0001.0000.0350.0000.0000.0000.0000.0000.0250.0250.0290.0700.0440.0000.1220.206
hardship_status1.0000.0000.0000.1561.0000.4020.1490.0000.0000.1270.0000.0840.0900.0600.5040.0001.0000.2450.0940.4990.0800.0000.0000.0000.0250.0630.1310.2300.9980.0680.1320.0000.1991.0000.0421.0000.0000.0000.0000.0000.0000.0000.1260.1900.1880.0000.0000.6040.1180.0000.0960.0000.0000.0000.0530.1190.0000.0310.1010.0000.0000.0000.0000.0000.0000.0000.0000.0340.0000.0000.0530.0001.0001.0000.0380.0370.0000.0910.0000.1670.0960.0000.0000.2210.2900.2900.0000.1060.0000.0000.1170.9180.0840.0000.4660.0590.0001.0000.0000.0000.1930.2181.0000.1510.0000.0000.5830.0000.4830.6360.0000.0000.0000.0001.0000.0001.0000.0000.0570.0000.0550.0000.0000.1530.1530.0000.0000.1620.0000.0580.000
home_ownership0.0050.0350.1100.0380.0060.1180.0810.0790.0250.0190.0000.0000.0000.0140.0640.0100.0000.0220.0000.0300.0900.0450.0450.0810.0810.0370.0660.0000.0030.0700.0000.1140.1060.0421.0001.0000.0310.0450.0420.0460.0080.0670.0390.0470.0470.0480.0810.0300.0000.0820.0970.0000.0200.0920.0290.0030.0290.0270.0180.0000.0270.0170.0000.0160.0310.0270.0460.0210.0390.0550.0320.0580.0000.0050.0000.0230.0610.0330.0320.0290.0430.0000.0100.0000.0340.0340.0160.0220.0000.0040.0850.0000.0000.0260.1190.0240.0000.0590.1610.1610.0690.2780.0330.0890.0930.0720.0170.0800.0360.0250.0980.0440.0000.1070.0000.0920.0230.0990.0310.0290.0390.0630.0310.0670.0670.0410.0030.0660.0340.0270.029
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il_util-0.0170.2500.0140.554-0.064-0.0840.0000.074-0.051-0.0610.0080.0530.0070.0080.052-0.031-0.0200.018-0.040-0.0170.040-0.121-0.121-0.098-0.0980.061-0.022-0.0480.000-0.0020.000-0.0980.0000.0000.031-0.0571.0000.0220.1840.2070.099-0.0900.160-0.109-0.109-0.008-0.0980.038-0.135-0.021-0.113-0.065-0.218-0.0430.0610.009-0.066-0.443-0.0520.065-0.0990.0680.073-0.083-0.069-0.066-0.0710.220-0.044-0.056-0.0700.0950.0000.0000.0030.2680.0940.2140.2100.4120.3630.0670.0890.004-0.105-0.105-0.030-0.0540.0290.0230.0060.0000.053-0.149-0.081-0.071-0.0200.011-0.084-0.0840.073-0.0270.004-0.034-0.0040.041-0.037-0.058-0.0180.048-0.0460.0540.0070.0390.0400.1030.0070.0980.2800.424-0.1250.0300.168-0.031-0.031-0.0210.023-0.041-0.1200.0720.023
initial_list_status0.0120.0110.0370.0490.0090.0710.0910.0230.0470.0920.0020.0180.0040.0280.0610.0090.0060.0850.0150.0600.0370.0890.0890.1130.1120.1400.0000.0000.0000.1470.0000.0800.0340.0000.0451.0000.0221.0000.0270.0340.0820.0610.1370.0920.0920.0630.1120.2550.0000.0250.0370.0220.0180.0150.0000.0380.0550.0090.0190.0230.0380.0150.0000.0120.0240.0310.0150.0070.0220.0130.0220.0300.0080.0110.0070.0200.0410.0410.0030.0320.0180.0270.0280.0000.2520.2520.0180.0960.0000.0060.0650.0000.0190.0110.0680.0850.0000.0320.1060.1060.0320.0710.0000.0000.0000.0000.0360.0300.1520.1000.1960.1440.0060.1530.0000.0280.0000.0190.0310.0140.0500.0110.0350.0920.0900.0420.0120.1140.0230.0840.000
inq_fi-0.0030.3190.0470.0800.1200.0800.0140.1350.027-0.0830.0080.0270.0080.0130.0390.014-0.0070.0070.1020.1130.009-0.047-0.047-0.002-0.0020.0450.193-0.0650.000-0.0060.0000.0900.0000.0000.0420.0460.1840.0271.0000.4800.2120.0060.134-0.084-0.0840.031-0.0020.021-0.0840.010-0.032-0.073-0.1740.1110.0240.039-0.043-0.333-0.0660.048-0.2260.0510.080-0.0090.0030.0220.0500.2180.0610.0670.0110.1310.0070.000-0.0020.2480.1300.1610.1970.3140.4190.0810.1130.191-0.017-0.017-0.042-0.0780.0790.0740.0210.0000.027-0.0730.001-0.0940.0050.024-0.062-0.0620.1100.0680.0220.0180.0540.072-0.0420.025-0.0130.0000.0400.0430.0250.0220.0510.1720.1580.1730.1840.259-0.0340.1020.225-0.021-0.021-0.0010.016-0.037-0.0140.0350.028
inq_last_12m0.0060.4310.0400.0260.1320.0750.0070.1050.051-0.1190.0120.0570.0180.0090.0510.035-0.0000.0130.0360.0350.010-0.127-0.1270.0040.0040.0550.1640.0430.0000.1090.0710.1120.0950.0000.046-0.0570.2070.0340.4801.0000.5400.0180.171-0.147-0.1470.0650.0040.040-0.1030.017-0.041-0.275-0.3770.1260.0200.011-0.104-0.357-0.2180.041-0.6770.0360.0900.0560.1040.1030.1250.1730.1630.1650.0990.2000.0000.0000.0250.5170.2010.3650.1380.3920.3100.3300.3070.146-0.087-0.087-0.061-0.1080.1200.1090.0200.0000.057-0.060-0.070-0.136-0.0040.034-0.104-0.1040.1840.0500.0360.0190.0410.050-0.0790.010-0.0690.0000.0340.0510.0390.0120.0590.1720.1630.2190.1590.219-0.0180.0890.1780.0470.0470.0480.0320.0300.0250.0480.036
inq_last_6mths-0.0030.2770.026-0.0400.0430.0400.038-0.0260.017-0.0740.0070.0690.0100.0000.0690.021-0.0030.033-0.0060.0150.002-0.108-0.108-0.035-0.0360.0720.0610.0030.0000.0570.000-0.0180.0780.0000.008-0.1110.0990.0820.2120.5401.000-0.0140.191-0.127-0.1270.034-0.0350.171-0.0900.006-0.017-0.323-0.3530.0320.020-0.014-0.088-0.178-0.2240.044-0.6980.0360.0560.0630.1130.0970.1200.0720.1380.1470.1030.1370.0060.0000.0350.3240.1360.4100.0600.1630.1420.3100.2710.051-0.108-0.108-0.049-0.0620.0810.0720.0330.0000.072-0.050-0.022-0.0850.0060.022-0.073-0.0730.2960.008-0.0100.0150.0260.033-0.038-0.0220.0200.034-0.0250.0850.0240.0000.0370.0280.0300.1440.0360.076-0.0300.0320.0480.0210.0200.0350.0230.0080.0040.0510.018
installment0.0010.0100.0210.0340.4400.3620.1020.2370.1780.080-0.0070.040-0.0230.0100.0400.014-0.0000.0440.0620.0750.0280.0740.0740.9640.9630.0700.7660.0540.0200.3290.0000.8400.0280.0000.0670.012-0.0900.0610.0060.018-0.0141.0000.1090.0710.0710.4780.9640.0240.3820.1140.1610.0320.0180.191-0.0260.0090.0170.0060.017-0.050-0.005-0.038-0.0500.2050.1700.2150.2030.1000.1760.1790.1690.1910.0000.016-0.022-0.0160.194-0.0140.081-0.0050.028-0.024-0.0090.7540.1690.1690.0490.062-0.065-0.0780.0910.0000.0390.4420.3870.137-0.061-0.0690.1610.161-0.0770.1660.1000.2110.2130.0600.0470.768-0.0580.1440.3020.0670.0190.301-0.0710.2900.3150.2000.3170.1630.3640.0600.1990.6650.6650.6660.0100.5660.3820.1520.142
int_rate0.0230.1660.0110.319-0.134-0.1660.055-0.087-0.3720.3060.0180.1690.0230.0510.2100.0740.0160.1630.1880.2250.005-0.431-0.4310.0900.0900.6860.571-0.0140.0150.2460.0000.2470.0000.1260.039-0.0790.1600.1370.1340.1710.1910.1091.000-0.388-0.3880.0440.0900.079-0.075-0.063-0.145-0.117-0.144-0.112-0.047-0.036-0.015-0.153-0.092-0.026-0.159-0.0300.0790.0160.083-0.076-0.1000.003-0.028-0.0700.082-0.0300.0300.0090.0470.178-0.0260.1280.0540.1570.1480.1140.1300.583-0.029-0.029-0.1010.3000.0700.0590.0630.0020.173-0.020-0.0220.2880.0790.080-0.399-0.3990.095-0.132-0.124-0.098-0.0350.0470.2980.311-0.0200.0850.1580.7280.0270.3650.057-0.091-0.155-0.0600.0160.059-0.2810.0090.0000.0660.0660.3900.077-0.069-0.2530.1850.097
last_fico_range_high-0.015-0.1500.022-0.2540.0840.0640.0720.1080.313-0.226-0.027-0.404-0.0480.1870.672-0.119-0.0160.074-0.063-0.0730.0150.4270.4270.1020.1030.172-0.000-0.2030.018-0.1200.1280.0620.1360.1900.0470.121-0.1090.092-0.084-0.147-0.1270.071-0.3881.0001.0000.1830.1020.3050.1200.0460.1390.1070.1040.1070.0830.0780.1230.0750.0940.0530.1070.058-0.118-0.044-0.1030.0390.055-0.0090.0040.037-0.1010.0100.0070.004-0.078-0.1350.008-0.097-0.019-0.076-0.079-0.116-0.1440.0390.1480.1480.173-0.217-0.101-0.0850.0380.015-0.4090.0690.073-0.213-0.030-0.0820.3890.389-0.1170.0640.0210.0380.0230.009-0.2080.160-0.0580.208-0.1230.182-0.0400.042-0.1030.1020.1560.0320.025-0.0140.2720.0080.0200.1200.121-0.072-0.1870.2010.2560.0900.000
last_fico_range_low-0.015-0.1500.023-0.2540.0840.0640.0720.1080.313-0.226-0.027-0.404-0.0480.1870.672-0.119-0.0160.074-0.063-0.0730.0150.4270.4270.1020.1030.172-0.000-0.2030.018-0.1200.1190.0620.1260.1880.0470.121-0.1090.092-0.084-0.147-0.1270.071-0.3881.0001.0000.1830.1020.3060.1200.0460.1390.1070.1040.1070.0830.0780.1230.0750.0940.0530.1070.058-0.118-0.044-0.1030.0390.055-0.0090.0040.037-0.1010.0100.0070.004-0.078-0.1350.008-0.097-0.019-0.076-0.079-0.116-0.1440.0390.1480.1480.173-0.217-0.101-0.0850.0350.015-0.4090.0690.073-0.213-0.030-0.0820.3890.389-0.1170.0640.0210.0380.0230.009-0.2080.160-0.0580.209-0.1230.182-0.0400.042-0.1030.1020.1560.0320.025-0.0140.2720.0080.0200.1200.121-0.072-0.1870.2010.2560.0900.000
last_pymnt_amnt-0.0000.0620.0130.0200.2580.2540.0770.1750.0910.0230.004-0.157-0.0230.0690.2160.002-0.0020.082-0.0220.0010.0170.0420.0420.4620.4610.0500.494-0.0890.0000.2020.0710.4830.0000.0000.048-0.203-0.0080.0630.0310.0650.0340.4780.0440.1830.1831.0000.4620.2070.2060.0630.091-0.006-0.0220.1730.0050.020-0.015-0.049-0.0060.015-0.0330.008-0.0090.0670.0480.1000.1590.1080.0870.1470.0470.1030.0000.011-0.0110.0410.1050.0290.0560.0500.0810.0170.0260.504-0.323-0.3230.0260.022-0.005-0.0140.0280.000-0.1620.1990.2470.045-0.051-0.0530.1280.128-0.0580.1570.0560.1520.1550.0520.0110.574-0.0911.0000.1980.0440.0160.202-0.0380.1980.2060.1790.1750.1210.1720.0650.1170.6050.6050.258-0.0800.6340.1850.0740.078
loan_amnt0.001-0.0050.0230.0090.4630.4020.1370.2700.2160.053-0.0090.036-0.0260.0160.0510.004-0.0010.0940.0560.0590.0320.1270.1271.0000.9990.0710.7950.0620.0040.3790.0000.8820.0000.0000.0810.023-0.0980.112-0.0020.004-0.0350.9640.0900.1020.1020.4621.0000.0490.3990.1370.1860.0520.0320.225-0.0200.0190.0270.0130.036-0.0450.009-0.033-0.0590.1990.1600.2190.2120.1200.1780.1880.1590.2010.0000.006-0.030-0.0350.204-0.0280.088-0.0130.023-0.044-0.0320.7860.2180.2180.0640.038-0.075-0.0850.0950.0000.0340.4570.4180.114-0.066-0.0860.2330.233-0.0860.2140.1250.2380.2400.0870.0090.823-0.0620.1360.3250.0630.0130.440-0.0800.3240.3540.2220.3380.1740.3980.0720.2170.6610.6610.7010.0050.5470.4180.1550.173
loan_status0.0000.0420.0250.0300.0000.0000.1860.0140.0220.0400.0000.1240.0000.3251.0000.0000.0000.1940.0050.0420.0170.1100.1100.0490.0510.1000.0690.1410.2060.0000.1350.1150.1590.6040.0301.0000.0380.2550.0210.0400.1710.0240.0790.3050.3060.2070.0491.0000.0000.0190.0330.0230.0210.0300.0060.0110.0990.0160.0200.0300.0310.0210.0020.0150.0230.0040.0380.0050.0170.0330.0220.0120.0000.0000.0000.0340.0100.0290.0070.0290.0360.0320.0360.0720.2830.2830.0140.0460.0000.0100.0710.1970.1280.0080.0000.0330.0000.0340.0700.0700.0690.0220.0000.0000.0190.0000.0770.0090.0150.1080.0770.0930.0000.1800.0000.0150.0000.0290.0140.0160.0240.0090.0220.1580.1570.0240.0600.1980.0070.0830.055
max_bal_bc-0.004-0.0980.0000.1570.3780.3040.0000.2940.2040.386-0.025-0.022-0.0610.0000.008-0.050-0.0030.0180.1720.1570.0100.0760.0760.3990.3990.0000.2680.0490.0000.0550.0000.3590.0000.1180.000-0.010-0.1350.000-0.084-0.103-0.0900.382-0.0750.1200.1200.2060.3990.0001.0000.1490.2580.1010.1050.2220.0150.0640.0830.0760.070-0.0180.086-0.004-0.1420.3300.2240.2920.2650.0860.1780.1920.2210.2070.0000.000-0.063-0.1130.207-0.1060.084-0.073-0.044-0.099-0.1090.2520.1530.1530.1370.309-0.130-0.1240.0000.000-0.0220.7910.5510.406-0.058-0.0870.1980.198-0.1090.2030.0840.1420.1530.0290.1120.355-0.0170.0000.1420.000-0.0260.000-0.1580.3440.3600.1990.4090.1240.645-0.0010.1780.2630.2630.260-0.0200.2310.5620.0041.000
mo_sin_old_il_acct0.0160.0050.0380.0600.2170.1990.0040.2010.0280.0590.020-0.0120.0090.0000.0180.0860.0140.0210.0670.0690.0520.0240.0240.1370.1370.0220.0750.0830.0000.0800.0730.0930.0000.0000.082-0.016-0.0210.0250.0100.0170.0060.114-0.0630.0460.0460.0630.1370.0190.1491.0000.2900.011-0.0160.233-0.008-0.007-0.064-0.0210.031-0.010-0.011-0.0130.1180.0400.0710.0400.1340.4370.0720.1690.0700.1530.0160.0000.0570.0130.1550.0160.2040.0320.053-0.016-0.0360.0870.0280.028-0.1420.0530.0400.0290.0180.000-0.0130.1610.1860.068-0.018-0.0080.0950.095-0.0100.1650.0530.1230.1150.0870.0040.156-0.0280.0000.0600.0190.0220.0860.0190.2430.2470.3730.2570.2280.1050.1190.2420.1020.1020.087-0.0100.0920.1360.0210.032
mo_sin_old_rev_tl_op0.031-0.0560.017-0.0620.2380.2300.0300.1770.1570.0170.034-0.034-0.0130.0050.0430.1070.0230.0140.0630.0460.0830.1120.1120.1860.1860.0540.079-0.0100.0060.0460.1400.1540.0000.0960.097-0.039-0.1130.037-0.032-0.041-0.0170.161-0.1450.1390.1390.0910.1860.0330.2580.2901.0000.0360.0110.344-0.053-0.007-0.1640.0160.0680.0160.012-0.0070.0960.1210.1640.1590.3570.0460.2100.4140.1610.1650.0040.0190.051-0.0280.169-0.009-0.025-0.007-0.002-0.044-0.0800.1230.0190.019-0.1430.0370.0440.0410.0240.000-0.0330.2990.2770.0330.014-0.0400.1680.168-0.0200.2250.0440.2710.132-0.008-0.0240.1080.0010.0440.0310.0480.0150.081-0.0220.2160.2560.3450.1460.0180.2740.0690.0390.1610.1610.104-0.0120.1600.3270.0400.054
mo_sin_rcnt_rev_tl_op0.000-0.5200.0140.1450.0150.0060.0350.131-0.1270.169-0.000-0.055-0.0170.0090.0400.0140.0010.0000.0040.0140.0090.1070.1070.0520.0520.0300.0710.1010.0000.0670.0000.0950.0000.0000.0000.035-0.0650.022-0.073-0.275-0.3230.032-0.1170.1070.107-0.0060.0520.0230.1010.0110.0361.0000.7620.010-0.069-0.0350.0940.0700.706-0.0880.247-0.067-0.069-0.175-0.271-0.225-0.202-0.011-0.330-0.271-0.267-0.2640.0000.000-0.007-0.643-0.265-0.6780.008-0.068-0.060-0.824-0.6780.0830.0680.0680.0360.137-0.079-0.0690.0120.000-0.0560.0210.0340.199-0.026-0.0280.1040.104-0.1300.0500.001-0.080-0.0660.0130.1220.0650.0140.022-0.0100.023-0.0170.010-0.0670.0210.000-0.1850.013-0.009-0.035-0.0130.0080.0120.0120.004-0.0070.018-0.0960.0280.000
mo_sin_rcnt_tl0.001-0.5300.0000.040-0.062-0.0550.0250.000-0.1070.167-0.005-0.058-0.0140.0040.0330.0020.0000.017-0.061-0.0600.0030.0730.0730.0320.0320.0310.0000.0530.0000.0340.0450.0410.0000.0000.0200.018-0.2180.018-0.174-0.377-0.3530.018-0.1440.1040.104-0.0220.0320.0210.105-0.0160.0110.7621.000-0.062-0.055-0.0260.0620.4440.509-0.0770.335-0.060-0.066-0.093-0.173-0.148-0.149-0.150-0.233-0.207-0.169-0.2570.0000.000-0.010-0.705-0.257-0.850-0.141-0.389-0.300-0.596-0.469-0.0050.0590.0590.0370.137-0.068-0.0600.0090.000-0.0590.050-0.0050.187-0.000-0.0170.0430.043-0.140-0.023-0.019-0.057-0.066-0.0500.1260.027-0.0450.0000.0010.023-0.0160.010-0.056-0.096-0.101-0.231-0.113-0.172-0.011-0.085-0.1300.0090.009-0.005-0.0120.021-0.0670.0230.034
mort_acc0.0270.0940.0320.0080.3590.3230.0070.6400.1020.0270.033-0.033-0.0170.0040.0240.1100.0200.013-0.011-0.0230.0420.0890.0890.2250.2250.0210.150-0.0710.000-0.0010.1060.2190.0000.0000.092-0.074-0.0430.0150.1110.1260.0320.191-0.1120.1070.1070.1730.2250.0300.2220.2330.3440.010-0.0621.000-0.073-0.044-0.121-0.0840.041-0.020-0.047-0.0330.0930.0370.0700.0650.2010.1700.0980.2450.0690.1660.0000.0050.0520.0820.1680.0750.0730.0870.122-0.014-0.0340.182-0.024-0.024-0.1080.0310.0060.0070.0250.000-0.0330.2540.2510.051-0.044-0.0650.2310.231-0.0420.6620.1230.1980.1650.080-0.0550.161-0.0390.0250.0260.022-0.0060.052-0.0210.6550.6630.3920.2230.1510.1940.1930.1530.2060.2060.123-0.0220.2020.2540.0290.000
mths_since_last_delinq-0.1440.1230.0000.020-0.070-0.1040.000-0.0720.0150.001-0.118-0.010-0.0480.0000.004-0.820-0.1240.0000.0090.0700.0170.1050.105-0.020-0.0200.027-0.014-0.0420.000-0.0190.0000.0050.0000.0530.0290.0370.0610.0000.0240.0200.020-0.026-0.0470.0830.0830.005-0.0200.0060.015-0.008-0.053-0.069-0.055-0.0731.0000.691-0.051-0.043-0.0920.759-0.0000.8660.0660.0290.0020.023-0.005-0.019-0.018-0.0470.002-0.0480.0400.063-0.3460.096-0.0500.046-0.0260.0430.0570.0760.0990.0370.0150.0150.197-0.0040.0960.1020.0220.000-0.008-0.0050.064-0.005-0.121-0.0620.1450.1450.028-0.0490.3100.0310.039-0.017-0.0330.001-0.1020.0430.0340.0260.0070.0100.059-0.084-0.097-0.057-0.030-0.0120.0160.000-0.043-0.045-0.045-0.056-0.045-0.036-0.0010.0200.071
mths_since_last_major_derog-0.0990.1330.020-0.006-0.022-0.1240.016-0.0290.053-0.003-0.211-0.013-0.1430.0000.019-0.543-0.0760.0150.0320.1280.0180.0880.0880.0190.0190.0230.0890.0820.0000.1020.0000.0550.0810.1190.0030.0560.0090.0380.0390.011-0.0140.009-0.0360.0780.0780.0200.0190.0110.064-0.007-0.007-0.035-0.026-0.0440.6911.0000.071-0.049-0.0610.5810.0260.555-0.0580.0500.0340.042-0.005-0.0380.038-0.0350.0400.0070.0930.026-0.6910.0630.0040.006-0.0230.0450.0810.0310.0800.1030.0280.0280.127-0.0000.0820.0730.0150.000-0.0140.0410.085-0.021-0.107-0.0100.1730.173-0.002-0.0320.462-0.0550.0180.0100.003-0.029-0.0640.000-0.0720.0190.0190.0200.055-0.025-0.027-0.0630.0000.0040.0630.012-0.010-0.012-0.012-0.021-0.028-0.0100.0600.0140.038
mths_since_last_record-0.008-0.0980.053-0.047-0.061-0.0450.0750.0300.0190.043-0.029-0.054-0.0310.0100.037-0.0670.0010.0740.0780.1760.0270.2720.2720.0270.0320.0470.195-0.1140.0000.0880.0000.1620.0000.0000.0290.128-0.0660.055-0.043-0.104-0.0880.017-0.0150.1230.123-0.0150.0270.0990.083-0.064-0.1640.0940.062-0.121-0.0510.0711.0000.0130.097-0.0730.074-0.101-0.1980.0090.018-0.011-0.186-0.0350.022-0.1730.0290.0290.0000.000-0.073-0.1050.017-0.0740.027-0.0310.010-0.119-0.1300.1660.1200.1200.2500.059-0.3130.3130.0600.011-0.0470.1060.2520.032-0.033-0.0830.2490.249-0.105-0.089-0.049-0.0690.0700.0580.0800.1000.0180.0000.0380.042-0.3240.046-0.0730.0380.045-0.1710.0150.0050.0690.0280.016-0.104-0.098-0.067-0.051-0.1040.1000.0550.075
mths_since_rcnt_il0.007-0.4420.000-0.193-0.153-0.0990.015-0.145-0.0410.100-0.014-0.0450.0000.0020.0240.0130.0080.037-0.220-0.1950.0090.0000.0000.0130.0130.021-0.130-0.0700.000-0.0660.000-0.0490.0000.0310.0270.016-0.4430.009-0.333-0.357-0.1780.006-0.1530.0750.075-0.0490.0130.0160.076-0.0210.0160.0700.444-0.084-0.043-0.0490.0131.0000.061-0.0630.185-0.052-0.0200.0240.005-0.020-0.035-0.357-0.040-0.0520.008-0.1850.0000.0000.013-0.489-0.185-0.421-0.403-0.857-0.769-0.070-0.087-0.1310.0610.061-0.0060.086-0.050-0.0490.0120.000-0.0450.067-0.0680.1030.039-0.003-0.009-0.009-0.079-0.038-0.0710.005-0.051-0.1290.057-0.0630.0140.0000.0100.013-0.0140.027-0.020-0.202-0.177-0.225-0.333-0.4560.018-0.175-0.371-0.003-0.003-0.010-0.0140.013-0.0080.0130.032
mths_since_recent_bc0.008-0.4770.0000.1600.0060.0300.0370.132-0.2410.2260.003-0.053-0.0130.0090.0370.0470.0080.0130.0190.0000.0170.0560.0560.0360.0350.0210.0590.0510.0030.0830.1580.0890.1550.1010.0180.003-0.0520.019-0.066-0.218-0.2240.017-0.0920.0940.094-0.0060.0360.0200.0700.0310.0680.7060.5090.041-0.092-0.0610.0970.0611.000-0.1060.159-0.096-0.051-0.301-0.243-0.365-0.2770.004-0.298-0.227-0.238-0.2380.0000.0000.018-0.525-0.238-0.4900.009-0.059-0.055-0.674-0.6240.0800.0470.0470.0030.182-0.038-0.0230.0160.005-0.0530.0090.0280.198-0.014-0.0150.0800.080-0.1030.058-0.011-0.063-0.0620.0250.1350.0660.0150.0000.0050.015-0.0110.015-0.0450.0320.006-0.1430.012-0.005-0.1480.0190.0090.0170.0170.013-0.0110.022-0.1210.0160.039
mths_since_recent_bc_dlq-0.1030.1630.0100.034-0.068-0.0920.035-0.043-0.0370.019-0.049-0.011-0.0140.0000.022-0.632-0.0810.0190.0090.0720.0180.0060.006-0.045-0.0450.0170.043-0.1980.0050.0010.1050.1010.0440.0000.0000.0010.0650.0230.0480.0410.044-0.050-0.0260.0530.0530.015-0.0450.030-0.018-0.0100.016-0.088-0.077-0.0200.7590.581-0.073-0.063-0.1061.000-0.0110.8870.235-0.0280.002-0.0390.026-0.014-0.0060.0160.003-0.0270.0170.065-0.2260.115-0.0290.070-0.0120.0590.0800.0860.1350.029-0.011-0.0110.0560.0130.1040.0970.0120.000-0.011-0.026-0.028-0.004-0.043-0.0520.0930.0930.048-0.0260.3750.027-0.012-0.0240.005-0.0630.0170.0000.0000.0090.0160.0000.087-0.050-0.063-0.004-0.0230.008-0.0510.010-0.023-0.041-0.041-0.052-0.034-0.031-0.0320.0270.000
mths_since_recent_inq0.002-0.1950.0310.032-0.062-0.0410.015-0.011-0.0320.091-0.004-0.056-0.0100.0000.059-0.0310.0010.0220.0210.0290.0000.0770.0770.0090.0090.065-0.150-0.0530.000-0.0960.000-0.1080.0000.0000.0270.032-0.0990.038-0.226-0.677-0.698-0.005-0.1590.1070.107-0.0330.0090.0310.086-0.0110.0120.2470.335-0.047-0.0000.0260.0740.1850.159-0.0111.000-0.013-0.051-0.021-0.051-0.059-0.073-0.072-0.086-0.095-0.044-0.0920.0000.000-0.033-0.278-0.094-0.323-0.043-0.172-0.111-0.225-0.170-0.1680.0570.0570.0460.080-0.067-0.0580.0260.000-0.0550.0580.0690.097-0.012-0.0600.0550.055-0.1980.003-0.0060.0140.013-0.0020.067-0.016-0.0000.000-0.0110.054-0.0260.013-0.029-0.046-0.048-0.112-0.044-0.0770.023-0.037-0.056-0.012-0.012-0.027-0.0240.003-0.0020.0430.040
mths_since_recent_revol_delinq-0.1290.1250.0000.046-0.058-0.0770.033-0.033-0.0230.018-0.056-0.008-0.0160.0000.009-0.721-0.1070.000-0.0020.0570.0140.0380.038-0.033-0.0330.0250.073-0.1160.005-0.0290.0000.1080.0000.0000.0170.0250.0680.0150.0510.0360.036-0.038-0.0300.0580.0580.008-0.0330.021-0.004-0.013-0.007-0.067-0.060-0.0330.8660.555-0.101-0.052-0.0960.887-0.0131.0000.212-0.004-0.026-0.0120.020-0.013-0.053-0.028-0.026-0.0660.0220.061-0.2100.099-0.0680.048-0.0120.0530.0660.0690.0930.1160.0080.0080.0820.0070.0950.0950.0140.000-0.008-0.0380.0380.012-0.053-0.0300.1240.1240.045-0.0260.2980.0620.027-0.014-0.010-0.003-0.0750.0000.0760.0220.0030.0000.078-0.054-0.070-0.037-0.0260.007-0.031-0.003-0.025-0.051-0.051-0.056-0.040-0.042-0.0500.0160.000
num_accts_ever_120_pd0.0290.0780.0000.0650.0440.0530.0130.021-0.109-0.0080.1440.0200.0680.0000.0000.2020.0160.004-0.058-0.0570.007-0.270-0.270-0.059-0.0590.020-0.106-0.1000.000-0.0230.000-0.1500.0000.0000.000-0.0040.0730.0000.0800.0900.056-0.0500.079-0.118-0.118-0.009-0.0590.002-0.1420.1180.096-0.069-0.0660.0930.066-0.058-0.198-0.020-0.0510.235-0.0510.2121.000-0.057-0.021-0.0770.0500.097-0.0220.072-0.0160.0060.0280.0000.3220.0840.0060.0720.0510.0360.0360.0810.087-0.122-0.026-0.026-0.594-0.016-0.002-0.0450.0120.0000.018-0.148-0.106-0.0140.0690.048-0.143-0.1430.0490.0590.0880.024-0.028-0.0230.017-0.0720.0020.0000.0210.0160.0250.0140.1160.0220.0060.126-0.0140.053-0.1830.0120.035-0.026-0.026-0.0070.027-0.028-0.1720.0160.000
num_actv_bc_tl-0.0090.2020.028-0.0350.1980.1660.053-0.0820.2990.067-0.0160.022-0.0130.0120.024-0.032-0.0060.0400.1730.1910.029-0.092-0.0920.1990.1990.0040.0600.0110.000-0.0100.0800.1200.0000.0000.016-0.042-0.0830.012-0.0090.0560.0630.2050.016-0.044-0.0440.0670.1990.0150.3300.0400.121-0.175-0.0930.0370.0290.0500.0090.024-0.301-0.028-0.021-0.004-0.0571.0000.7950.8410.595-0.0150.6390.4440.7900.5340.0000.000-0.0330.1410.5340.1100.022-0.031-0.0100.2310.307-0.0090.0260.0260.0920.079-0.050-0.0630.0460.0000.0240.5100.3730.120-0.013-0.0390.0230.023-0.0070.0500.0650.2020.235-0.015-0.0020.146-0.0240.0000.0570.0080.0080.040-0.0380.1210.1570.2910.2060.0340.544-0.0760.0360.1510.1510.166-0.0120.1290.4710.0290.000
num_actv_rev_tl0.0030.3130.021-0.0150.1550.1510.051-0.1150.1300.131-0.0020.044-0.0010.0230.0470.0160.0040.0310.2590.2500.042-0.178-0.1780.1600.1600.0320.076-0.0590.0000.0040.0420.0960.0000.0000.031-0.073-0.0690.0240.0030.1040.1130.1700.083-0.103-0.1030.0480.1600.0230.2240.0710.164-0.271-0.1730.0700.0020.0340.0180.005-0.2430.002-0.051-0.026-0.0210.7951.0000.6540.4920.0230.7920.5770.9910.6580.0000.000-0.0060.2360.6600.1790.036-0.0090.0170.3250.4140.032-0.001-0.0010.0370.1410.001-0.0090.0430.0000.0450.5260.3730.128-0.004-0.016-0.055-0.0550.0190.0610.0500.2260.2550.0030.0410.156-0.0280.0710.0620.0270.0080.045-0.0010.1320.1610.3990.2120.0460.3360.0290.0390.1400.1400.180-0.0040.1110.4640.0430.033
num_bc_sats-0.0080.2740.024-0.2140.2220.1860.039-0.0990.536-0.196-0.0110.007-0.0060.0000.000-0.032-0.0070.0270.1170.1430.0260.0660.0660.2190.2190.0290.109-0.0270.0000.0610.0000.1700.0000.0000.027-0.007-0.0660.0310.0220.1030.0970.215-0.0760.0390.0390.1000.2190.0040.2920.0400.159-0.225-0.1480.0650.0230.042-0.011-0.020-0.365-0.039-0.059-0.012-0.0770.8410.6541.0000.7360.0050.7490.5670.6460.6240.0000.000-0.0320.2060.6250.1720.0210.0100.0310.2870.3750.0460.0330.0330.114-0.136-0.051-0.0570.0260.0000.0090.4310.344-0.120-0.018-0.0360.1070.1070.0040.0460.0280.2570.271-0.008-0.1700.173-0.0380.0320.0550.026-0.0000.036-0.0360.1330.2040.3850.1970.0510.663-0.0610.0520.1510.1510.118-0.0260.1400.5890.0240.000
num_bc_tl0.0150.2640.025-0.2160.2490.2130.065-0.0120.427-0.1610.0290.018-0.0120.0040.0040.0430.0090.0000.0920.0900.0360.0360.0360.2120.2120.0370.044-0.0870.0000.0240.0000.1030.0000.0000.046-0.145-0.0710.0150.0500.1250.1200.203-0.1000.0550.0550.1590.2120.0380.2650.1340.357-0.202-0.1490.201-0.005-0.005-0.186-0.035-0.2770.026-0.0730.0200.0500.5950.4920.7361.0000.0840.6330.8290.4910.5320.0000.0000.0280.2030.5360.1750.0260.0350.0630.2590.3380.003-0.074-0.074-0.006-0.108-0.0050.0000.0280.0000.0210.3690.317-0.115-0.004-0.0330.1250.1250.0270.1340.0410.3590.225-0.028-0.1730.154-0.0260.0310.0110.033-0.0110.043-0.0340.1750.2400.6230.1870.0630.5340.0040.0620.2170.2170.128-0.0230.2130.5120.0240.005
num_il_tl0.0140.2730.0400.2340.2570.2480.0000.2490.0130.0200.0270.0200.0100.0040.0040.0840.0130.0130.2970.2540.0180.0100.0100.1200.1200.0080.0450.0220.0000.1220.0000.0220.0000.0340.021-0.0160.2200.0070.2180.1730.0720.1000.003-0.009-0.0090.1080.1200.0050.0860.4370.046-0.011-0.1500.170-0.019-0.038-0.035-0.3570.004-0.014-0.072-0.0130.097-0.0150.0230.0050.0841.0000.0590.1390.0230.3950.0000.0000.0560.2030.3950.1480.7000.3590.505-0.0000.0060.028-0.007-0.007-0.0750.022-0.006-0.0050.0210.0000.0170.0910.1790.023-0.011-0.0110.0940.094-0.0070.1610.0660.0700.1430.231-0.0460.1820.0110.0000.0370.000-0.0020.0530.0320.3730.3510.6650.5840.6530.0410.3090.6510.0900.0900.0700.0060.0750.0880.0100.019
num_op_rev_tl0.0110.4200.027-0.2460.1650.1700.035-0.1620.374-0.1480.0020.0230.0040.0210.0270.0230.0100.0280.1960.1840.0380.0130.0130.1780.1780.0140.135-0.1200.0000.0660.0000.1540.0000.0000.039-0.034-0.0440.0220.0610.1630.1380.176-0.0280.0040.0040.0870.1780.0170.1780.0720.210-0.330-0.2330.098-0.0180.0380.022-0.040-0.298-0.006-0.086-0.053-0.0220.6390.7920.7490.6330.0591.0000.7810.7940.8310.0000.000-0.0140.3110.8320.2450.0340.0330.0700.3940.5180.1080.0020.0020.067-0.0960.0130.0120.0320.0000.0250.4180.326-0.1960.007-0.0070.0430.0430.0350.0560.0030.2970.2940.012-0.1770.155-0.0290.0160.0350.013-0.0010.0450.0170.1360.2090.5560.1960.0640.4580.0550.0580.1390.1390.118-0.0220.1240.6060.0140.026
num_rev_accts0.0240.3560.021-0.2230.2120.2120.044-0.0350.317-0.1230.0410.023-0.0000.0200.0130.0930.0160.0000.1570.1360.0450.0070.0070.1880.1880.0230.054-0.1490.0000.0500.0580.0940.0000.0000.055-0.129-0.0560.0130.0670.1650.1470.179-0.0700.0370.0370.1470.1880.0330.1920.1690.414-0.271-0.2070.245-0.047-0.035-0.173-0.052-0.2270.016-0.095-0.0280.0720.4440.5770.5670.8290.1390.7811.0000.5760.6640.0000.0000.0510.2730.6680.2210.0460.0540.0910.3240.4210.039-0.076-0.076-0.046-0.0750.0350.0480.0280.0000.0260.3670.308-0.1580.016-0.0100.0810.0810.0460.1420.0140.3970.2540.010-0.1770.165-0.0280.051-0.0030.022-0.0160.037-0.0010.1940.2590.7670.1990.0850.3910.1090.0810.1980.1980.121-0.0200.1920.5250.0230.000
num_rev_tl_bal_gt_00.0020.3090.021-0.0100.1540.1510.049-0.1150.1340.132-0.0040.042-0.0040.0220.0460.0120.0030.0320.2600.2510.043-0.175-0.1750.1590.1590.0330.081-0.0650.0000.0060.0630.0910.0000.0530.032-0.074-0.0700.0220.0110.0990.1030.1690.082-0.101-0.1010.0470.1590.0220.2210.0700.161-0.267-0.1690.0690.0020.0400.0290.008-0.2380.003-0.044-0.026-0.0160.7900.9910.6460.4910.0230.7940.5761.0000.6610.0000.000-0.0120.2300.6610.1760.036-0.0110.0170.3210.4100.043-0.001-0.0010.0430.143-0.005-0.0160.0440.0000.0440.5290.3750.131-0.002-0.016-0.055-0.0550.0190.0620.0460.2270.2570.0040.0410.154-0.0180.0390.0530.0300.0080.0470.0010.1330.1620.3990.2140.0450.3370.0340.0400.1400.1400.179-0.0040.1110.4660.0370.042
num_sats0.0070.4670.025-0.0400.2680.2730.0190.0120.319-0.1010.0050.0230.0090.0140.0210.0600.0060.0220.3190.2690.0200.0540.0540.2010.2010.0170.165-0.1100.0000.0880.0000.1630.0000.0000.058-0.0180.0950.0300.1310.2000.1370.191-0.0300.0100.0100.1030.2010.0120.2070.1530.165-0.264-0.2570.166-0.0480.0070.029-0.185-0.238-0.027-0.092-0.0660.0060.5340.6580.6240.5320.3950.8310.6640.6611.0000.0000.0000.0070.3450.9990.2680.4680.1800.2630.3120.4150.1350.0180.0180.037-0.058-0.027-0.0310.0330.0000.0230.4020.371-0.134-0.011-0.0070.0910.0910.0170.1180.0300.2580.3370.151-0.1480.192-0.0290.0000.0270.015-0.0040.0690.0190.3590.4100.7090.4850.3900.4170.1150.3960.1470.1470.128-0.0120.1280.5490.0110.032
num_tl_120dpd_2m0.3480.0000.0190.0000.0000.0000.0000.0000.0000.0000.0560.0000.0000.0000.0000.0220.3570.0000.0000.0000.0110.0110.0110.0000.0000.0131.0001.0000.0001.0001.0001.0001.0001.0000.0001.0000.0000.0080.0070.0000.0060.0000.0300.0070.0070.0000.0000.0000.0000.0160.0040.0000.0000.0000.0400.0930.0000.0000.0000.0170.0000.0220.0280.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0490.0000.0000.0000.0000.0000.0090.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0370.0370.0000.0000.0000.0000.0000.0000.0001.0001.0001.0001.0000.0280.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0120.0120.0070.0000.0000.0000.0110.000
num_tl_30dpd0.8930.0000.0000.0000.0000.0000.0050.0000.0000.0140.0000.0000.0000.0060.0000.0520.0120.0050.0000.0000.0040.0130.0130.0060.0070.0111.0001.0000.0001.0001.0001.0001.0001.0000.0051.0000.0000.0110.0000.0000.0000.0160.0090.0040.0040.0110.0060.0000.0000.0000.0190.0000.0000.0050.0630.0260.0000.0000.0000.0650.0000.0610.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0210.0040.0000.0000.0040.0000.0000.0000.1200.0080.0000.0000.0000.0000.0080.0260.0000.0450.0000.0000.0220.2730.1740.0000.0000.0100.0000.0030.0000.0000.0000.0030.0000.0000.0000.0290.0000.0250.0260.0120.0000.0150.0000.0080.000
num_tl_90g_dpd_24m0.088-0.0350.0000.0140.0310.0740.0000.020-0.0670.0040.2720.0170.1430.0000.0000.5110.0640.004-0.026-0.0290.007-0.156-0.156-0.030-0.0300.014-0.083-0.0650.003-0.0650.209-0.0880.2500.0380.000-0.0250.0030.007-0.0020.0250.035-0.0220.047-0.078-0.078-0.011-0.0300.000-0.0630.0570.051-0.007-0.0100.052-0.346-0.691-0.0730.0130.018-0.226-0.033-0.2100.322-0.033-0.006-0.0320.0280.056-0.0140.051-0.0120.0070.0490.0001.000-0.0040.0090.0190.025-0.008-0.0250.002-0.017-0.110-0.023-0.023-0.2600.001-0.012-0.0190.0140.0060.017-0.064-0.0590.0070.1110.038-0.109-0.1090.0190.040-0.1680.028-0.0020.016-0.002-0.032-0.0400.0000.0090.0150.0050.0080.0130.0210.0170.079-0.0020.016-0.0900.0050.025-0.006-0.0060.0050.028-0.008-0.0830.0140.000
num_tl_op_past_12m-0.0030.7450.013-0.0250.0910.0720.0260.0050.127-0.1850.0050.0720.0150.0200.072-0.023-0.0050.0120.0880.0580.011-0.104-0.104-0.035-0.0350.0670.102-0.0720.0060.0440.0000.0270.0920.0370.023-0.0110.2680.0200.2480.5170.324-0.0160.178-0.135-0.1350.041-0.0350.034-0.1130.013-0.028-0.643-0.7050.0820.0960.063-0.105-0.489-0.5250.115-0.2780.0990.0840.1410.2360.2060.2030.2030.3110.2730.2300.3450.0000.000-0.0041.0000.3460.7070.1870.5670.4240.7960.6220.108-0.073-0.073-0.034-0.1570.0990.0880.0160.0010.071-0.0400.013-0.211-0.0160.018-0.078-0.0780.1320.0430.0610.0720.0960.055-0.1300.0130.0090.0470.0130.0600.0250.0000.0660.1340.1380.3070.1600.2270.0260.1130.175-0.011-0.0110.0010.017-0.0250.0940.0800.031
open_acc0.0170.4680.025-0.0390.2710.2730.0170.0120.317-0.1010.0060.0210.0110.0160.0200.0630.0170.0230.3230.2690.0210.0420.0420.2040.2040.0160.161-0.1060.0000.0860.0000.1620.0000.0000.061-0.0010.0940.0410.1300.2010.1360.194-0.0260.0080.0080.1050.2040.0100.2070.1550.169-0.265-0.2570.168-0.0500.0040.017-0.185-0.238-0.029-0.094-0.0680.0060.5340.6600.6250.5360.3950.8320.6680.6610.9990.0000.0000.0090.3461.0000.2680.4680.1800.2620.3130.4160.1330.0230.0230.035-0.058-0.016-0.0200.0340.0000.0200.4020.370-0.134-0.010-0.0070.0900.0900.0180.1190.0310.2590.3360.150-0.1480.189-0.0340.0000.0320.015-0.0020.0700.0190.3580.4090.7130.4850.3900.4150.1150.3960.1470.1470.129-0.0120.1280.5470.0110.031
open_acc_6m-0.0050.5320.005-0.0370.0750.0700.0230.0160.130-0.1820.0170.0470.0130.0020.0540.005-0.0030.0090.0420.0540.008-0.057-0.057-0.028-0.0280.0540.061-0.0860.0000.0430.072-0.0190.1630.0910.033-0.0360.2140.0410.1610.3650.410-0.0140.128-0.097-0.0970.029-0.0280.029-0.1060.016-0.009-0.678-0.8500.0750.0460.006-0.074-0.421-0.4900.070-0.3230.0480.0720.1100.1790.1720.1750.1480.2450.2210.1760.2680.0000.0000.0190.7070.2681.0000.1340.3780.2830.5840.4530.032-0.069-0.069-0.038-0.1480.0640.0540.0150.0000.047-0.0380.010-0.189-0.0010.025-0.044-0.0440.1590.0140.0310.0690.0810.061-0.120-0.047-0.0200.067-0.0210.0540.0120.0000.0570.1170.1230.2420.1190.1660.0400.0820.1230.0090.0090.0070.0080.0000.0920.0510.008
open_act_il0.0140.2560.0160.3080.2560.2250.0000.201-0.0040.0570.0040.0230.0060.0000.0050.0560.0150.0000.4250.3330.0450.0390.0390.0880.0880.0090.1510.0540.0000.1840.0000.0820.0000.0000.032-0.0100.2100.0030.1970.1380.0600.0810.054-0.019-0.0190.0560.0880.0070.0840.204-0.0250.008-0.1410.073-0.026-0.0230.027-0.4030.009-0.012-0.043-0.0120.0510.0220.0360.0210.0260.7000.0340.0460.0360.4680.0000.0000.0250.1870.4680.1341.0000.3860.525-0.022-0.0100.1100.0280.028-0.0420.055-0.016-0.0160.0200.0000.0230.0970.1710.059-0.024-0.0020.0590.059-0.0080.0640.0760.0120.1490.3000.0000.113-0.0400.0000.0650.0140.0020.0160.0110.3600.3370.4190.6510.7590.0470.1850.7780.0520.0520.0770.0120.0310.0670.0130.027
open_il_12m-0.0070.4260.0200.1950.1470.1010.0020.1420.033-0.0900.0140.0450.0010.0000.046-0.007-0.0090.0190.1920.1780.016-0.011-0.011-0.013-0.0130.0550.1310.0230.0110.0550.0000.0370.0000.1670.029-0.0240.4120.0320.3140.3920.163-0.0050.157-0.076-0.0760.050-0.0130.029-0.0730.032-0.007-0.068-0.3890.0870.0430.045-0.031-0.857-0.0590.059-0.1720.0530.036-0.031-0.0090.0100.0350.3590.0330.054-0.0110.1800.0000.000-0.0080.5670.1800.3780.3861.0000.7050.0710.0800.138-0.063-0.063-0.010-0.0810.0480.0460.0150.0140.045-0.0640.062-0.091-0.032-0.0070.0060.0060.0820.0520.0730.0150.0690.138-0.0540.091-0.0820.0460.0020.0500.0160.0260.0220.1970.1720.2340.3150.418-0.0230.1770.3430.0070.0070.0150.021-0.0100.0030.0560.025
open_il_24m-0.0060.5740.0320.2180.2110.1400.0000.1830.035-0.0670.0090.048-0.0020.0000.050-0.017-0.0040.0240.2940.2590.016-0.000-0.0000.0230.0230.0580.1780.0640.0110.1370.0000.0700.0000.0960.043-0.0220.3630.0180.4190.3100.1420.0280.148-0.079-0.0790.0810.0230.036-0.0440.053-0.002-0.060-0.3000.1220.0570.0810.010-0.769-0.0550.080-0.1110.0660.036-0.0100.0170.0310.0630.5050.0700.0910.0170.2630.0090.000-0.0250.4240.2620.2830.5250.7051.0000.0610.0970.178-0.059-0.0590.003-0.0590.0660.0630.0200.0150.048-0.0230.097-0.072-0.0270.0150.0300.0300.0600.0790.0760.0220.0840.173-0.0650.141-0.0050.0000.0410.0530.0230.0480.0250.2640.2410.3350.4240.541-0.0030.2470.4800.0330.0330.0350.0170.0120.0340.0490.048
open_rv_12m-0.0050.6070.013-0.1550.001-0.0100.045-0.1480.151-0.1750.0020.0540.0150.0220.059-0.020-0.0060.000-0.011-0.0270.008-0.120-0.120-0.044-0.0440.048-0.046-0.1350.0000.0300.000-0.0910.1760.0000.000-0.0520.0670.0270.0810.3300.310-0.0240.114-0.116-0.1160.017-0.0440.032-0.099-0.016-0.044-0.824-0.596-0.0140.0760.031-0.119-0.070-0.6740.086-0.2250.0690.0810.2310.3250.2870.259-0.0000.3940.3240.3210.3120.0000.0000.0020.7960.3130.584-0.0220.0710.0611.0000.752-0.080-0.084-0.084-0.031-0.1420.0930.0810.0070.0000.0540.006-0.035-0.2000.0110.033-0.115-0.1150.115-0.0490.0150.0770.070-0.016-0.118-0.079-0.0150.0800.0100.0490.0200.0290.076-0.0190.0090.214-0.0080.0040.0750.008-0.0180.0120.0120.0040.0050.0060.1380.0570.013
open_rv_24m-0.0040.8100.014-0.171-0.000-0.0040.054-0.2000.175-0.1850.0040.0680.0180.0270.071-0.039-0.0050.0090.0140.0060.004-0.143-0.143-0.032-0.0320.0480.023-0.1360.0000.0130.000-0.0420.1710.0000.010-0.0590.0890.0280.1130.3070.271-0.0090.130-0.144-0.1440.026-0.0320.036-0.109-0.036-0.080-0.678-0.469-0.0340.0990.080-0.130-0.087-0.6240.135-0.1700.0930.0870.3070.4140.3750.3380.0060.5180.4210.4100.4150.0000.000-0.0170.6220.4160.453-0.0100.0800.0970.7521.000-0.030-0.091-0.091-0.013-0.1460.1240.1110.0020.0000.0680.026-0.008-0.2290.0330.023-0.115-0.1150.126-0.0500.0390.1210.105-0.028-0.142-0.029-0.0620.1130.0300.0450.0250.0240.091-0.0290.0020.2770.0070.0160.1000.014-0.0120.0210.0210.0170.0040.0120.1810.0520.000
orig_projected_additional_accrued_interestNaN0.1190.0000.0830.3880.0530.2410.2440.1100.0300.0270.092-0.0440.0000.000-0.071NaN0.0000.1130.4970.0030.0600.0600.7860.7850.2831.000-0.0100.2210.4300.0000.9260.0150.2210.0000.2410.0040.0000.1910.1460.0510.7540.5830.0390.0390.5040.7860.0720.2520.0870.1230.083-0.0050.1820.0370.1030.166-0.1310.0800.029-0.1680.116-0.122-0.0090.0320.0460.0030.0280.1080.0390.0430.1351.0001.000-0.1100.1080.1330.0320.1100.1380.178-0.080-0.0301.0000.3990.3990.0530.086-0.0210.0090.0000.1620.0930.2180.2870.010-0.393NaN-0.413-0.413-0.1420.4550.5000.3220.2690.1910.2800.976-0.4170.0000.7590.411-0.0510.441-0.0290.2680.2940.0330.2760.2200.210-0.0300.2410.5320.5320.8020.0400.2520.2420.1230.000
out_prncp-0.019-0.0670.017-0.0470.0920.2490.2520.0400.143-0.083-0.008-0.2300.0070.0760.206-0.023-0.0130.2530.0500.0900.0150.1130.1130.2190.2210.0340.305-0.0040.0280.1160.0000.3310.0000.2900.0340.685-0.1050.252-0.017-0.087-0.1080.169-0.0290.1480.148-0.3230.2180.2830.1530.0280.0190.0680.059-0.0240.0150.0280.1200.0610.047-0.0110.0570.008-0.0260.026-0.0010.033-0.074-0.0070.002-0.076-0.0010.0180.0000.000-0.023-0.0730.023-0.0690.028-0.063-0.059-0.084-0.0910.3991.0001.0000.028-0.093-0.045-0.0200.0280.025-0.2360.0780.316-0.065-0.045-0.0810.1990.199-0.0770.1130.1120.1440.1680.076-0.005-0.0570.0690.076-0.0010.035-0.0290.306-0.0140.0500.079-0.0580.0680.0370.1420.0040.071-0.341-0.3390.058-0.041-0.4020.1360.0830.150
out_prncp_inv-0.019-0.0670.017-0.0470.0920.2490.2520.0400.143-0.083-0.008-0.2300.0070.0760.206-0.023-0.0130.2530.0500.0900.0150.1140.1140.2190.2210.0340.305-0.0040.0280.1160.0000.3300.0000.2900.0340.685-0.1050.252-0.017-0.087-0.1080.169-0.0290.1480.148-0.3230.2180.2830.1530.0280.0190.0680.059-0.0240.0150.0280.1200.0610.047-0.0110.0570.008-0.0260.026-0.0010.033-0.074-0.0070.002-0.076-0.0010.0180.0000.000-0.023-0.0730.023-0.0690.028-0.063-0.059-0.084-0.0910.3991.0001.0000.028-0.093-0.045-0.0200.0280.025-0.2360.0780.316-0.065-0.045-0.0810.1990.199-0.0770.1130.1120.1440.1680.076-0.005-0.0570.0690.076-0.0010.035-0.0290.306-0.0140.0510.079-0.0580.0680.0370.1420.0040.071-0.341-0.3390.058-0.041-0.4020.1360.0830.150
pct_tl_nvr_dlq-0.059-0.0040.013-0.074-0.060-0.1000.018-0.0530.171-0.036-0.096-0.022-0.0630.0000.005-0.486-0.0500.0220.0750.0710.0090.3570.3570.0640.0650.0460.0460.0360.005-0.0200.0680.0810.0000.0000.0160.021-0.0300.018-0.042-0.061-0.0490.049-0.1010.1730.1730.0260.0640.0140.137-0.142-0.1430.0360.037-0.1080.1970.1270.250-0.0060.0030.0560.0460.082-0.5940.0920.0370.114-0.006-0.0750.067-0.0460.0430.0370.0000.021-0.260-0.0340.035-0.038-0.042-0.0100.003-0.031-0.0130.0530.0280.0281.000-0.0230.0040.0570.0290.002-0.0200.1650.101-0.027-0.046-0.0250.1880.188-0.032-0.095-0.061-0.0180.015-0.009-0.0650.0850.0530.0000.0400.041-0.0450.040-0.134-0.035-0.018-0.0870.039-0.0380.237-0.003-0.0300.0150.015-0.014-0.0510.0200.2230.0200.000
percent_bc_gt_75-0.014-0.1480.0240.5120.0100.0320.0460.109-0.6370.863-0.0100.066-0.0340.0300.0770.012-0.0130.0360.1710.1650.016-0.407-0.4070.0380.0380.1290.0990.0790.0080.0440.0000.0450.0860.1060.022-0.194-0.0540.096-0.078-0.108-0.0620.0620.300-0.217-0.2170.0220.0380.0460.3090.0530.0370.1370.1370.031-0.004-0.0000.0590.0860.1820.0130.0800.007-0.0160.0790.141-0.136-0.1080.022-0.096-0.0750.143-0.0580.0000.0040.001-0.157-0.058-0.1480.055-0.081-0.059-0.142-0.1460.086-0.093-0.093-0.0231.000-0.032-0.0330.0590.0100.0710.3050.1990.7460.010-0.038-0.166-0.166-0.0640.0940.008-0.0140.0340.0440.4550.009-0.0390.0000.0220.111-0.0070.062-0.0680.075-0.005-0.0380.1160.027-0.2030.0050.0200.1190.1190.2130.0340.077-0.1730.0960.043
pub_rec-0.0040.1210.020-0.011-0.032-0.0950.009-0.089-0.087-0.027-0.0120.0250.0080.0000.011-0.043-0.0030.012-0.039-0.0100.008-0.254-0.254-0.075-0.0740.007-0.0210.0500.0000.0610.000-0.0140.1250.0000.000-0.0050.0290.0000.0790.1200.081-0.0650.070-0.101-0.101-0.005-0.0750.000-0.1300.0400.044-0.079-0.0680.0060.0960.082-0.313-0.050-0.0380.104-0.0670.095-0.002-0.0500.001-0.051-0.005-0.0060.0130.035-0.005-0.0270.0000.000-0.0120.099-0.0160.064-0.0160.0480.0660.0930.124-0.021-0.045-0.0450.004-0.0321.0000.8420.0190.0000.023-0.166-0.139-0.0680.014-0.018-0.114-0.1140.014-0.0300.057-0.039-0.071-0.058-0.013-0.068-0.0280.0000.0160.0000.4230.0070.068-0.093-0.1020.016-0.088-0.005-0.1740.021-0.024-0.030-0.030-0.0150.000-0.031-0.1590.0150.023
pub_rec_bankruptcies-0.0100.1130.043-0.021-0.064-0.1080.003-0.099-0.080-0.031-0.0160.015-0.0060.0130.029-0.062-0.0080.011-0.023-0.0110.012-0.228-0.228-0.085-0.0840.0320.0080.0480.0000.0720.000-0.0210.0000.0000.0040.0260.0230.0060.0740.1090.072-0.0780.059-0.085-0.085-0.014-0.0850.010-0.1240.0290.041-0.069-0.0600.0070.1020.0730.313-0.049-0.0230.097-0.0580.095-0.045-0.063-0.009-0.0570.000-0.0050.0120.048-0.016-0.0310.0000.000-0.0190.088-0.0200.054-0.0160.0460.0630.0810.1110.009-0.020-0.0200.057-0.0330.8421.0000.0060.0000.014-0.166-0.142-0.0780.013-0.015-0.103-0.1030.009-0.0370.064-0.038-0.075-0.059-0.023-0.061-0.0400.0130.0360.0310.0420.0150.018-0.104-0.1140.024-0.093-0.011-0.1650.032-0.028-0.066-0.066-0.047-0.012-0.064-0.1500.0210.018
purpose0.0000.0200.0210.0450.0000.0500.0320.0210.0150.0680.0000.0090.0030.0160.0470.0090.0000.1260.0000.0610.0200.0430.0430.0950.0970.0770.0000.0480.0260.0000.0000.0000.0970.1170.0851.0000.0060.0650.0210.0200.0330.0910.0630.0380.0350.0280.0950.0710.0000.0180.0240.0120.0090.0250.0220.0150.0600.0120.0160.0120.0260.0140.0120.0460.0430.0260.0280.0210.0320.0280.0440.0330.0000.0040.0140.0160.0340.0150.0200.0150.0200.0070.0020.0000.0280.0280.0290.0590.0190.0061.0000.0280.0030.0000.0750.0710.0640.0380.0670.0670.0350.0000.0480.0180.0730.0630.0710.0680.0990.0000.0610.0550.0120.1000.0000.0220.0040.0330.0110.0080.0180.0080.0100.0610.0610.0430.0000.0550.0110.0620.044
pymnt_plan0.0000.0000.0220.0000.0000.0000.0070.0000.0000.0000.0000.0000.0040.0000.0480.0000.0000.0000.0000.0410.0070.0000.0000.0000.0000.0000.0820.2650.9060.0000.0570.0000.1570.9180.0001.0000.0000.0000.0000.0000.0000.0000.0020.0150.0150.0000.0000.1970.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0010.0000.0000.0000.0140.0150.0000.0000.1620.0250.0250.0020.0100.0000.0000.0281.0000.0000.0000.0000.0000.0000.0000.0000.0000.0830.0001.0000.0000.0000.0000.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0040.0150.0000.0070.0000.0000.000
recoveries0.0080.0800.0000.070-0.042-0.0590.000-0.043-0.0840.0650.0010.9790.0080.3560.3460.0190.0100.0180.0510.0200.000-0.107-0.1070.0340.0330.0590.0700.1860.0000.0860.0000.0830.3190.0840.000-0.1800.0530.0190.0270.0570.0720.0390.173-0.409-0.409-0.1620.0340.128-0.022-0.013-0.033-0.056-0.059-0.033-0.008-0.014-0.047-0.045-0.053-0.011-0.055-0.0080.0180.0240.0450.0090.0210.0170.0250.0260.0440.0230.0000.0000.0170.0710.0200.0470.0230.0450.0480.0540.0680.093-0.236-0.236-0.0200.0710.0230.0140.0030.0001.000-0.008-0.0210.0640.0100.044-0.092-0.0920.104-0.040-0.024-0.008-0.006-0.0010.0350.356-0.0540.257-0.1470.0560.0180.1080.013-0.034-0.0500.0210.0060.024-0.0680.0130.001-0.088-0.0880.0470.152-0.215-0.0580.0450.009
revol_bal-0.004-0.0030.0230.1870.4140.3440.0000.2830.1960.340-0.022-0.010-0.0510.0000.000-0.043-0.0020.0270.2700.2680.0050.0180.0180.4570.4560.0100.259-0.0050.0000.1310.0000.3270.0000.0000.026-0.039-0.1490.011-0.073-0.060-0.0500.442-0.0200.0690.0690.1990.4570.0080.7910.1610.2990.0210.0500.254-0.0050.0410.1060.0670.009-0.0260.058-0.038-0.1480.5100.5260.4310.3690.0910.4180.3670.5290.4020.0000.000-0.064-0.0400.402-0.0380.097-0.064-0.0230.0060.0260.2180.0780.0780.1650.305-0.166-0.1660.0000.000-0.0081.0000.6520.446-0.056-0.0820.1400.140-0.0820.2120.0760.2230.2420.0460.1760.412-0.0380.0000.1200.000-0.0280.013-0.1540.4050.4240.3260.4890.1390.6380.0900.1630.3380.3380.333-0.0220.2950.7340.0160.018
revol_bal_joint-0.0020.0590.0000.1140.3240.4911.0000.2350.2180.206-0.023-0.021-0.0550.0000.000-0.058-0.0090.0980.2480.4460.0380.0610.0610.4180.4180.0000.3360.1250.0410.2530.0000.5600.4680.4660.1190.075-0.0810.0680.001-0.070-0.0220.387-0.0220.0730.0730.2470.4180.0000.5510.1860.2770.034-0.0050.2510.0640.0850.252-0.0680.028-0.0280.0690.038-0.1060.3730.3730.3440.3170.1790.3260.3080.3750.3710.0000.120-0.0590.0130.3700.0100.1710.0620.097-0.035-0.0080.2870.3160.3160.1010.199-0.139-0.1420.0750.000-0.0210.6521.0000.274-0.078-0.1070.2270.227-0.0110.2610.1170.4530.5030.2310.1640.091-0.1380.0000.4500.000-0.0140.105-0.1340.3730.4090.3390.4320.2060.5040.1320.2480.1840.1840.238-0.0290.1410.5460.0680.072
revol_util-0.017-0.2230.0170.6720.0860.0900.0460.193-0.6100.863-0.0090.060-0.0390.0290.0630.010-0.0140.0480.1780.1760.015-0.420-0.4200.1140.1140.1250.0510.1040.0000.0440.0530.0360.0000.0590.024-0.182-0.0710.085-0.094-0.136-0.0850.1370.288-0.213-0.2130.0450.1140.0330.4060.0680.0330.1990.1870.051-0.005-0.0210.0320.1030.198-0.0040.0970.012-0.0140.1200.128-0.120-0.1150.023-0.196-0.1580.131-0.1340.0050.0080.007-0.211-0.134-0.1890.059-0.091-0.072-0.200-0.2290.010-0.065-0.065-0.0270.746-0.068-0.0780.0710.0000.0640.4460.2741.000-0.016-0.051-0.141-0.141-0.0820.1160.050-0.0260.0270.0390.5160.123-0.0420.0000.0730.108-0.0030.068-0.0920.1250.023-0.0870.1830.040-0.1520.0280.0410.1660.1660.2630.0360.119-0.1800.0990.054
sec_app_chargeoff_within_12_mths-0.0050.0060.000-0.018-0.017-0.0281.000-0.052-0.0290.0010.2010.0100.0180.0000.0000.080-0.0060.000-0.025-0.0160.000-0.045-0.045-0.066-0.0660.068-0.3780.1720.000-0.1720.000-0.4470.0000.0000.000-0.028-0.0200.0000.005-0.0040.006-0.0610.079-0.030-0.030-0.051-0.0660.000-0.058-0.0180.014-0.026-0.000-0.044-0.121-0.107-0.0330.039-0.014-0.043-0.012-0.0530.069-0.013-0.004-0.018-0.004-0.0110.0070.016-0.002-0.0110.0000.0000.111-0.016-0.010-0.001-0.024-0.032-0.0270.0110.033-0.393-0.045-0.045-0.0460.0100.0140.0130.0640.0000.010-0.056-0.078-0.0161.0000.138-0.193-0.1930.036-0.053-0.372-0.033-0.070-0.0100.058NaNNaN1.000NaN0.1550.0230.0070.006-0.050-0.050-0.001-0.051-0.036-0.049-0.035-0.034-0.041-0.041-0.0100.047-0.052-0.0460.0000.000
sec_app_collections_12_mths_ex_med-0.0080.0170.056-0.019-0.026-0.0401.000-0.065-0.023-0.0500.0010.0450.0850.0860.0950.039-0.0090.000-0.016-0.0180.016-0.045-0.045-0.086-0.0860.040NaNNaN0.000NaN1.000NaN1.0001.0000.059-0.0470.0110.0320.0240.0340.022-0.0690.080-0.082-0.082-0.053-0.0860.034-0.087-0.008-0.040-0.028-0.017-0.065-0.062-0.010-0.083-0.003-0.015-0.052-0.060-0.0300.048-0.039-0.016-0.036-0.033-0.011-0.007-0.010-0.016-0.0070.0000.0000.0380.018-0.0070.025-0.002-0.0070.0150.0330.023NaN-0.081-0.081-0.025-0.038-0.018-0.0150.0380.0000.044-0.082-0.107-0.0510.1381.000-0.274-0.2740.038-0.091-0.218-0.061-0.0660.0010.068-0.0710.0000.4530.5570.0630.0180.0150.084-0.062-0.068-0.015-0.043-0.015-0.073-0.001-0.024-0.048-0.048-0.0240.079-0.057-0.0680.0000.000
sec_app_fico_range_high-0.005-0.0480.038-0.1590.1210.1601.0000.2200.314-0.171-0.059-0.092-0.0760.0000.155-0.142-0.0060.0400.0370.0430.0190.4500.4500.2330.2320.184-0.3720.2110.007-0.2470.4700.1450.2730.0000.1610.102-0.0840.106-0.062-0.104-0.0730.161-0.3990.3890.3890.1280.2330.0700.1980.0950.1680.1040.0430.2310.1450.1730.249-0.0090.0800.0930.0550.124-0.1430.023-0.0550.1070.1250.0940.0430.081-0.0550.0910.0370.000-0.109-0.0780.090-0.0440.0590.0060.030-0.115-0.115-0.4130.1990.1990.188-0.166-0.114-0.1030.0670.000-0.0920.1400.227-0.141-0.193-0.2741.0001.000-0.1300.2940.4280.1700.1920.096-0.4030.2010.2750.000-0.0130.171-0.0550.099-0.1420.2390.2800.1250.1440.0900.3170.0810.1230.0890.090-0.025-0.1290.1450.2980.0380.027
sec_app_fico_range_low-0.005-0.0480.038-0.1590.1210.1601.0000.2200.314-0.171-0.059-0.092-0.0760.0000.155-0.142-0.0060.0400.0370.0430.0190.4500.4500.2330.2320.184-0.3720.2110.007-0.2470.4700.1450.2730.0000.1610.102-0.0840.106-0.062-0.104-0.0730.161-0.3990.3890.3890.1280.2330.0700.1980.0950.1680.1040.0430.2310.1450.1730.249-0.0090.0800.0930.0550.124-0.1430.023-0.0550.1070.1250.0940.0430.081-0.0550.0910.0370.000-0.109-0.0780.090-0.0440.0590.0060.030-0.115-0.115-0.4130.1990.1990.188-0.166-0.114-0.1030.0670.000-0.0920.1400.227-0.141-0.193-0.2741.0001.000-0.1300.2940.4280.1700.1920.096-0.4030.2010.2750.000-0.0130.171-0.0550.099-0.1420.2390.2800.1250.1440.0900.3170.0810.1230.0890.090-0.025-0.1290.1450.2980.0380.027
sec_app_inq_last_6mths0.0110.1270.000-0.018-0.0100.0251.000-0.0530.013-0.0730.0150.104-0.0250.0290.125-0.0060.0030.000-0.0290.0310.000-0.054-0.054-0.086-0.0860.044-0.1820.0000.083-0.0050.0000.1840.0000.1930.069-0.0190.0730.0320.1100.1840.296-0.0770.095-0.117-0.117-0.058-0.0860.069-0.109-0.010-0.020-0.130-0.140-0.0420.028-0.002-0.105-0.079-0.1030.048-0.1980.0450.049-0.0070.0190.0040.027-0.0070.0350.0460.0190.0170.0000.0080.0190.1320.0180.159-0.0080.0820.0600.1150.126-0.142-0.077-0.077-0.032-0.0640.0140.0090.0350.0830.104-0.082-0.011-0.0820.0360.038-0.130-0.1301.000-0.0560.0070.1290.1370.099-0.053-0.247-0.2750.0000.4670.0540.0200.0410.053-0.041-0.0420.021-0.0090.019-0.0480.0340.005-0.059-0.059-0.0280.099-0.079-0.0400.0200.026
sec_app_mort_acc0.0280.0800.0430.0670.1260.3011.0000.4670.0450.0960.000-0.040-0.0340.0000.0320.0870.0150.0430.1110.0020.0240.0340.0340.2140.2140.0390.378-0.2080.000-0.1150.1510.6170.3790.2180.278-0.012-0.0270.0710.0680.0500.0080.166-0.1320.0640.0640.1570.2140.0220.2030.1650.2250.050-0.0230.662-0.049-0.032-0.089-0.0380.058-0.0260.003-0.0260.0590.0500.0610.0460.1340.1610.0560.1420.0620.1180.0000.0260.0400.0430.1190.0140.0640.0520.079-0.049-0.0500.4550.1130.113-0.0950.094-0.030-0.0370.0000.000-0.0400.2120.2610.116-0.053-0.0910.2940.294-0.0561.0000.1600.2770.2310.097-0.0530.659-0.1970.0000.4280.013-0.0100.084-0.0690.4910.4900.2710.1920.1260.1460.1580.1460.1470.1470.070-0.0520.1540.1660.0240.036
sec_app_mths_since_last_major_derog0.0290.0720.0000.0510.0590.0541.0000.1350.0450.025-0.070-0.024-0.0070.0000.000-0.1290.0290.0000.0730.0660.026-0.046-0.0460.1250.1240.0340.500-0.3001.000-0.5000.0000.5000.0001.0000.0330.0450.0040.0000.0220.036-0.0100.100-0.1240.0210.0210.0560.1250.0000.0840.0530.0440.001-0.0190.1230.3100.462-0.049-0.071-0.0110.375-0.0060.2980.0880.0650.0500.0280.0410.0660.0030.0140.0460.0300.0000.000-0.1680.0610.0310.0310.0760.0730.0760.0150.0390.5000.1120.112-0.0610.0080.0570.0640.0481.000-0.0240.0760.1170.050-0.372-0.2180.4280.4280.0070.1601.0000.0970.110-0.008-0.059-1.0000.5001.000-0.5000.0000.0040.0770.0910.1270.1220.0450.1150.1150.0680.0520.1180.0610.0610.036-0.0300.0790.0480.0000.000
sec_app_num_rev_accts0.0120.1170.064-0.0620.1660.2841.0000.0800.196-0.0460.003-0.008-0.0280.0000.0000.0070.0010.0430.0570.2370.0120.0590.0590.2380.2380.0360.345-0.2510.0000.3670.4100.6730.1720.1510.089-0.025-0.0340.0000.0180.0190.0150.211-0.0980.0380.0380.1520.2380.0000.1420.1230.271-0.080-0.0570.1980.031-0.055-0.0690.005-0.0630.0270.0140.0620.0240.2020.2260.2570.3590.0700.2970.3970.2270.2580.0000.0450.0280.0720.2590.0690.0120.0150.0220.0770.1210.3220.1440.144-0.018-0.014-0.039-0.0380.0180.000-0.0080.2230.453-0.026-0.033-0.0610.1700.1700.1290.2770.0971.0000.7460.182-0.1640.1660.0440.3200.5260.027-0.0050.076-0.0380.1810.2170.3160.1650.0790.2480.0970.0980.1550.1550.124-0.0210.1500.2980.0330.028
sec_app_open_acc-0.0050.1420.0810.0190.1750.3311.0000.1140.1490.015-0.021-0.006-0.0060.0410.040-0.021-0.0170.0280.1060.3550.0310.0440.0440.2400.2400.0000.206-0.3070.0000.0440.4470.4300.4470.0000.093-0.017-0.0040.0000.0540.0410.0260.213-0.0350.0230.0230.1550.2400.0190.1530.1150.132-0.066-0.0660.1650.0390.0180.070-0.051-0.062-0.0120.0130.027-0.0280.2350.2550.2710.2250.1430.2940.2540.2570.3370.0000.000-0.0020.0960.3360.0810.1490.0690.0840.0700.1050.2690.1680.1680.0150.034-0.071-0.0750.0730.000-0.0060.2420.5030.027-0.070-0.0660.1920.1920.1370.2310.1100.7461.0000.573-0.1080.1700.2930.4240.4830.000-0.0180.108-0.0070.2450.2710.2720.2560.1800.2340.1150.1980.1590.1590.166-0.0110.1410.2790.0240.020
sec_app_open_act_il-0.0220.0760.0630.1040.0670.2431.0000.116-0.0150.042-0.004-0.001-0.0110.0000.0000.006-0.0320.0000.1660.3480.0380.0450.0450.0870.0870.0000.148-0.0760.0220.1620.1400.1620.7260.0000.0720.0260.0410.0000.0720.0500.0330.0600.0470.0090.0090.0520.0870.0000.0290.087-0.0080.013-0.0500.080-0.0170.0100.058-0.1290.025-0.024-0.002-0.014-0.023-0.0150.003-0.008-0.0280.2310.0120.0100.0040.1510.0000.0000.0160.0550.1500.0610.3000.1380.173-0.016-0.0280.1910.0760.076-0.0090.044-0.058-0.0590.0630.000-0.0010.0460.2310.039-0.0100.0010.0960.0960.0990.097-0.0080.1820.5731.0000.0540.1240.1700.0000.1720.032-0.0280.070-0.0010.1720.1700.1500.2530.2810.0160.1580.2950.0390.0390.0780.0200.0200.0320.0000.037
sec_app_revol_util-0.045-0.1550.0430.355-0.0090.0231.0000.049-0.4230.4780.0150.035-0.0030.0000.0600.029-0.0280.0350.0720.1270.023-0.307-0.3070.0090.0090.1340.209-0.1720.0000.0460.0000.0460.0000.5830.017-0.074-0.0370.036-0.042-0.079-0.0380.0470.298-0.208-0.2080.0110.0090.0770.1120.004-0.0240.1220.126-0.055-0.0330.0030.0800.0570.1350.0050.067-0.0100.017-0.0020.041-0.170-0.173-0.046-0.177-0.1770.041-0.1480.0000.022-0.002-0.130-0.148-0.1200.000-0.054-0.065-0.118-0.1420.280-0.005-0.005-0.0650.455-0.013-0.0230.0710.0000.0350.1760.1640.5160.0580.068-0.403-0.403-0.053-0.053-0.059-0.164-0.1080.0541.0000.055-0.5270.286-0.4050.1270.0200.025-0.031-0.014-0.054-0.1330.032-0.031-0.1920.009-0.0220.0310.0310.1520.053-0.029-0.1890.0600.068
settlement_amount0.0110.0360.0000.1040.4070.1540.1840.2670.1480.063-0.0300.3550.0621.0000.000-0.0030.0160.0000.1170.3070.0000.0900.0900.8230.8230.1450.9020.4021.0000.1400.0000.9720.4700.0000.0800.155-0.0580.0300.0250.010-0.0220.7680.3110.1600.1600.5740.8230.0090.3550.1560.1080.0650.0270.1610.001-0.0290.100-0.0630.066-0.063-0.016-0.003-0.0720.1460.1560.1730.1540.1820.1550.1650.1540.1921.0000.273-0.0320.0130.189-0.0470.1130.0910.141-0.079-0.0290.976-0.057-0.0570.0850.009-0.068-0.0610.0681.0000.3560.4120.0910.123NaN-0.0710.2010.201-0.2470.659-1.0000.1660.1700.1240.0551.0000.1410.1850.3960.134-0.0140.483-0.0440.3160.3330.2230.3730.2570.3050.0600.2620.4770.4760.516-0.0780.1420.3720.0750.000
settlement_percentage0.0870.0060.092-0.031-0.031-0.4220.000-0.0240.043-0.039-0.027-0.051-0.0401.0000.0000.0450.0750.1330.0230.3170.0000.0270.027-0.062-0.0630.000-0.176-0.4721.000-0.0500.000-0.2120.0000.4830.0360.181-0.0180.152-0.013-0.0690.020-0.058-0.020-0.058-0.058-0.091-0.0620.015-0.017-0.0280.0010.014-0.045-0.039-0.102-0.0640.0180.0140.0150.017-0.000-0.0750.002-0.024-0.028-0.038-0.0260.011-0.029-0.028-0.018-0.0291.0000.174-0.0400.009-0.034-0.020-0.040-0.082-0.005-0.015-0.062-0.4170.0690.0690.053-0.039-0.028-0.0400.0991.000-0.054-0.038-0.138-0.042NaN0.0000.2750.275-0.275-0.1970.5000.0440.2930.170-0.5270.1411.0000.1580.0710.000-0.0110.088-0.010-0.029-0.016-0.023-0.014-0.0610.0020.047-0.006-0.076-0.078-0.0730.175-0.076-0.0210.0000.000
settlement_status0.0280.0440.1230.0930.0000.1730.0730.0000.0000.0370.0000.2550.0371.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.1360.1420.0520.3400.4281.0000.1640.0000.0000.0000.6360.0251.0000.0480.1000.0000.0000.0340.1440.0850.2080.2091.0000.1360.1080.0000.0000.0440.0220.0000.0250.0430.0000.0000.0000.0000.0000.0000.0000.0000.0000.0710.0320.0310.0000.0160.0510.0390.0001.0000.0000.0000.0470.0000.0670.0000.0460.0000.0800.1130.0000.0760.0760.0000.0000.0000.0130.0001.0000.2570.0000.0000.0001.0000.4530.0000.0000.0000.0001.0000.3200.4240.0000.2860.1850.1581.0000.4300.0520.0000.1180.0650.0000.0000.0000.0000.0590.0000.0000.0330.0400.0350.1060.0360.0790.0000.0000.076
settlement_term-0.0400.0420.0880.0510.144-0.0540.0630.0580.0100.0600.026-0.1440.0511.0000.000-0.059-0.0310.0000.0360.2670.0000.0110.0110.3250.3260.0790.7350.1761.0000.2370.0000.6250.0000.0000.0980.386-0.0460.1960.0400.034-0.0250.3020.158-0.123-0.1230.1980.3250.0770.1420.0600.031-0.0100.0010.0260.034-0.0720.0380.0100.0050.000-0.0110.0760.0210.0570.0620.0550.0110.0370.035-0.0030.0530.0271.0000.0000.0090.0130.032-0.0210.0650.0020.0410.0100.0300.759-0.001-0.0010.0400.0220.0160.0360.0611.000-0.1470.1200.4500.073NaN0.557-0.013-0.0130.4670.428-0.5000.5260.4830.172-0.4050.3960.0710.4301.0000.069-0.0160.274-0.0120.0650.0690.0420.0950.1370.0850.0340.0700.0880.0890.251-0.0950.0650.0850.0000.000
sub_grade0.0180.0590.0100.1130.0000.0480.0330.0160.0880.1190.0000.0520.0160.0660.2340.0200.0000.1930.0000.0830.0110.1830.1830.0620.0631.0000.3140.0000.0080.1420.0000.0500.0000.0000.0441.0000.0540.1440.0430.0510.0850.0670.7280.1820.1820.0440.0630.0930.0000.0190.0480.0230.0230.0220.0260.0190.0420.0130.0150.0090.0540.0220.0160.0080.0270.0260.0330.0000.0130.0220.0300.0150.0280.0100.0150.0600.0150.0540.0140.0500.0530.0490.0450.4110.0350.0350.0410.1110.0000.0310.0550.0000.0560.0000.0000.1080.1550.0630.1710.1710.0540.0130.0000.0270.0000.0320.1270.1340.0000.0520.0691.0000.0000.3910.0000.0250.0060.0210.0100.0150.0760.0170.0090.0670.0670.1680.0220.0460.0360.1920.110
tax_liens0.0030.0270.0140.0090.0560.0050.000-0.002-0.021-0.002-0.0040.0200.0130.0000.0000.0180.0020.001-0.032-0.0000.008-0.078-0.0780.0130.0130.004-0.0140.0390.0000.0610.0420.0130.2020.0000.000-0.0330.0070.0060.0250.0390.0240.0190.027-0.040-0.0400.0160.0130.000-0.0260.0220.015-0.017-0.016-0.0060.0070.019-0.324-0.014-0.0110.016-0.0260.0030.0250.0080.008-0.000-0.011-0.002-0.001-0.0160.008-0.0040.0000.0000.0050.025-0.0020.0120.0020.0160.0230.0200.025-0.051-0.029-0.029-0.045-0.0070.4230.0420.0120.0000.018-0.028-0.014-0.0030.0230.018-0.055-0.0550.020-0.0100.004-0.005-0.018-0.0280.020-0.014-0.0110.000-0.0160.0001.0000.0020.056-0.002-0.003-0.0140.0020.018-0.037-0.0080.0140.0480.0480.0490.0200.041-0.0360.0110.030
term0.0040.0180.0500.0680.0000.0630.0670.0250.0050.0500.0000.0970.0140.0240.0920.0060.0070.0160.0160.0810.0600.0450.0450.4400.4380.3800.4130.0000.0000.3360.0000.3540.0000.0000.1071.0000.0390.1530.0220.0120.0000.3010.3650.0420.0420.2020.4400.1800.0000.0860.0810.0100.0100.0520.0100.0200.0460.0270.0150.0000.0130.0000.0140.0400.0450.0360.0430.0530.0450.0370.0470.0690.0000.0030.0080.0000.0700.0000.0160.0260.0480.0290.0240.4410.3060.3060.0400.0620.0070.0150.1000.0000.1080.0130.1050.0680.0070.0150.0990.0990.0410.0840.0770.0760.1080.0700.0250.4830.0880.1180.2740.3910.0021.0000.0000.0420.0000.0960.0600.0480.0170.0570.0600.2240.2240.4980.0190.1310.0150.0950.000
tot_coll_amt-0.0010.0760.000-0.012-0.039-0.0380.000-0.050-0.043-0.0690.0030.0150.2260.0090.0080.0230.0000.000-0.029-0.0140.007-0.246-0.246-0.080-0.0800.000-0.027-0.0820.000-0.0621.000-0.0581.0001.0000.0000.0160.0400.0000.0510.0590.037-0.0710.057-0.103-0.103-0.038-0.0800.000-0.1580.019-0.022-0.067-0.056-0.0210.0590.055-0.073-0.020-0.0450.087-0.0290.0780.116-0.038-0.001-0.036-0.0340.0320.017-0.0010.0010.0190.0000.0000.0130.0660.0190.0570.0110.0220.0250.0760.091-0.029-0.014-0.014-0.134-0.0680.0680.0180.0000.0000.013-0.154-0.134-0.0920.0060.084-0.142-0.1420.053-0.0690.091-0.038-0.007-0.001-0.031-0.044-0.0100.065-0.0120.0000.0560.0001.000-0.041-0.0450.013-0.0570.004-0.139-0.008-0.001-0.051-0.051-0.0290.006-0.050-0.1260.0041.000
tot_cur_bal0.0210.1660.0550.1940.5270.4910.0220.9260.1370.0780.014-0.033-0.0120.0130.0370.0880.0200.0230.1460.0880.0150.1330.1330.3240.3240.0250.2870.0220.0000.1360.1200.3490.0000.0000.092-0.0040.1030.0280.1720.1720.0280.290-0.0910.1020.1020.1980.3240.0150.3440.2430.2160.021-0.0960.655-0.084-0.0250.038-0.2020.032-0.050-0.046-0.0540.0220.1210.1320.1330.1750.3730.1360.1940.1330.3590.0130.0000.0210.1340.3580.1170.3600.1970.264-0.019-0.0290.2680.0500.051-0.0350.075-0.093-0.1040.0220.000-0.0340.4050.3730.125-0.050-0.0620.2390.239-0.0410.4910.1270.1810.2450.172-0.0140.316-0.0290.0000.0650.025-0.0020.042-0.0411.0000.9730.4270.6210.5170.3030.1960.5120.2360.2360.180-0.0070.2170.3690.0340.016
tot_hi_cred_lim0.0240.1760.0320.0440.5580.5230.0000.8760.259-0.0190.013-0.048-0.0120.0000.0100.0890.0230.0120.1430.0950.0000.2230.2230.3540.3540.0120.3140.0110.0000.1391.0000.3931.0001.0000.0230.0320.0070.0000.1580.1630.0300.315-0.1550.1560.1560.2060.3540.0000.3600.2470.2560.000-0.1010.663-0.097-0.0270.045-0.1770.006-0.063-0.048-0.0700.0060.1570.1610.2040.2400.3510.2090.2590.1620.4100.0000.0000.0170.1380.4090.1230.3370.1720.2410.0090.0020.2940.0790.079-0.018-0.005-0.102-0.1140.0040.000-0.0500.4240.4090.023-0.050-0.0680.2800.280-0.0420.4900.1220.2170.2710.170-0.0540.333-0.0160.0000.0690.006-0.0030.000-0.0450.9731.0000.4600.5930.4740.4050.1920.5020.2390.2390.165-0.0160.2250.4800.0210.027
total_acc0.0280.4040.031-0.0080.3320.3300.0280.1930.232-0.0710.0480.0200.0070.0170.0110.1290.0200.0050.2520.2130.0400.0200.0200.2210.2210.0240.047-0.0980.0000.0900.0000.0580.0350.0000.099-0.0950.0980.0190.1730.2190.1440.200-0.0600.0320.0320.1790.2220.0290.1990.3730.345-0.185-0.2310.392-0.057-0.063-0.171-0.225-0.143-0.004-0.112-0.0370.1260.2910.3990.3850.6230.6650.5560.7670.3990.7090.0000.0030.0790.3070.7130.2420.4190.2340.3350.2140.2770.033-0.058-0.058-0.087-0.0380.0160.0240.0330.0000.0210.3260.339-0.087-0.001-0.0150.1250.1250.0210.2710.0450.3160.2720.150-0.1330.223-0.0230.0000.0420.021-0.0140.0960.0130.4270.4601.0000.4950.4340.3080.2480.4290.2090.2090.135-0.0120.1970.4280.0270.025
total_bal_ex_mort0.0120.2200.0240.3850.5000.4220.0080.4800.1300.1300.0010.009-0.0180.0080.0220.0330.0130.0270.4490.4050.0120.0670.0670.3380.3380.0050.3040.0710.0000.2640.0000.3320.0000.0570.0310.0140.2800.0310.1840.1590.0360.3170.0160.0250.0250.1750.3380.0140.4090.2570.1460.013-0.1130.223-0.0300.0000.015-0.3330.012-0.023-0.044-0.026-0.0140.2060.2120.1970.1870.5840.1960.1990.2140.4850.0000.000-0.0020.1600.4850.1190.6510.3150.424-0.0080.0070.2760.0680.0680.0390.116-0.088-0.0930.0110.0000.0060.4890.4320.183-0.051-0.0430.1440.144-0.0090.1920.1150.1650.2560.2530.0320.373-0.0140.0000.0950.0100.0020.060-0.0570.6210.5930.4951.0000.8810.3400.1950.8630.2280.2280.2270.0030.1910.4060.0250.036
total_bal_il0.0080.2880.0170.3570.3710.3090.0140.4070.0450.0300.0070.024-0.0000.0000.0160.0490.0090.0150.4230.3640.0170.0380.0380.1740.1740.0100.2520.0810.0000.2960.0000.2270.0000.0000.029-0.0170.4240.0140.2590.2190.0760.1630.059-0.014-0.0140.1210.1740.0160.1240.2280.018-0.009-0.1720.151-0.0120.0040.005-0.456-0.0050.008-0.0770.0070.0530.0340.0460.0510.0630.6530.0640.0850.0450.3900.0000.0000.0160.2270.3900.1660.7590.4180.5410.0040.0160.2200.0370.037-0.0380.027-0.005-0.0110.0080.0000.0240.1390.2060.040-0.036-0.0150.0900.0900.0190.1260.1150.0790.1800.281-0.0310.257-0.0610.0590.1370.0150.0180.0480.0040.5170.4740.4340.8811.0000.1010.2010.9560.1200.1200.1310.0140.0920.1310.0260.024
total_bc_limit-0.0010.0520.021-0.2760.3850.3240.0120.1640.776-0.259-0.030-0.067-0.0450.0100.047-0.0890.0020.0490.0880.1040.0160.3730.3730.3980.3980.0770.2540.0140.0000.0960.0000.3820.0000.0550.0390.098-0.1250.050-0.034-0.018-0.0300.364-0.2810.2720.2720.1720.3980.0240.6450.1050.274-0.035-0.0110.1940.0160.0630.0690.018-0.148-0.0510.023-0.031-0.1830.5440.3360.6630.5340.0410.4580.3910.3370.4170.0000.000-0.0900.0260.4150.0400.047-0.023-0.0030.0750.1000.2100.1420.1420.237-0.203-0.174-0.1650.0180.000-0.0680.6380.504-0.152-0.049-0.0730.3170.317-0.0480.1460.0680.2480.2340.016-0.1920.3050.0020.0000.0850.076-0.0370.017-0.1390.3030.4050.3080.3400.1011.000-0.0230.1320.2280.2280.137-0.0600.2240.8760.0050.000
total_cu_tl0.0060.1550.0550.0620.1110.1080.0370.169-0.0120.0020.0160.013-0.0040.0000.0030.0230.0060.0220.1540.1660.0300.0110.0110.0720.0720.012-0.032-0.0430.0000.0660.179-0.0570.0000.0000.0630.0060.0300.0110.1020.0890.0320.0600.0090.0080.0080.0650.0720.009-0.0010.1190.069-0.013-0.0850.1930.0000.0120.028-0.1750.0190.010-0.037-0.0030.012-0.0760.029-0.0610.0040.3090.0550.1090.0340.1150.0000.0290.0050.1130.1150.0820.1850.1770.2470.0080.014-0.0300.0040.004-0.0030.0050.0210.0320.0080.0000.0130.0900.1320.028-0.035-0.0010.0810.0810.0340.1580.0520.0970.1150.1580.0090.0600.0470.0000.0340.017-0.0080.057-0.0080.1960.1920.2480.1950.201-0.0231.0000.2070.0410.0410.0280.0070.0310.0820.0270.022
total_il_high_credit_limit0.0170.2400.0200.2560.4150.3640.0300.3970.0640.0260.0100.0040.0030.0000.0200.0680.0170.0150.4580.3890.0130.0920.0920.2170.2170.0090.2710.0870.0000.2700.0000.2710.0000.0000.0310.0530.1680.0350.2250.1780.0480.1990.0000.0200.0200.1170.2170.0220.1780.2420.0390.008-0.1300.153-0.043-0.0100.016-0.3710.009-0.023-0.056-0.0250.0350.0360.0390.0520.0620.6510.0580.0810.0400.3960.0000.0000.0250.1750.3960.1230.7780.3430.480-0.018-0.0120.2410.0710.071-0.0300.020-0.024-0.0280.0100.0000.0010.1630.2480.041-0.034-0.0240.1230.1230.0050.1460.1180.0980.1980.295-0.0220.262-0.0060.0330.0700.0090.0140.060-0.0010.5120.5020.4290.8630.9560.1320.2071.0000.1250.1250.1280.0100.0990.1600.0180.031
total_pymnt0.0170.0030.0170.0630.3240.1880.0810.2020.0630.129-0.001-0.082-0.0260.0270.1510.0350.0100.1730.008-0.0120.0290.0170.0170.6610.6590.0760.525-0.0470.0000.2630.0440.5250.0250.1530.067-0.491-0.0310.092-0.0210.0470.0210.6650.0660.1200.1200.6050.6610.1580.2630.1020.1610.0120.0090.206-0.045-0.012-0.104-0.0030.017-0.041-0.012-0.051-0.0260.1510.1400.1510.2170.0900.1390.1980.1400.1470.0120.025-0.006-0.0110.1470.0090.0520.0070.0330.0120.0210.532-0.341-0.3410.0150.119-0.030-0.0660.0610.004-0.0880.3380.1840.166-0.041-0.0480.0890.089-0.0590.1470.0610.1550.1590.0390.0310.477-0.0760.0400.0880.0670.0480.224-0.0510.2360.2390.2090.2280.1200.2280.0410.1251.0000.9990.7240.0130.9660.2450.1510.040
total_pymnt_inv0.0170.0030.0170.0630.3240.1880.0810.2020.0630.129-0.001-0.083-0.0260.0280.1510.0350.0100.1730.009-0.0120.0290.0170.0170.6610.6610.0760.525-0.0470.0000.2630.0440.5250.0250.1530.067-0.488-0.0310.090-0.0210.0470.0200.6650.0660.1210.1210.6050.6610.1570.2630.1020.1610.0120.0090.206-0.045-0.012-0.098-0.0030.017-0.041-0.012-0.051-0.0260.1510.1400.1510.2170.0900.1390.1980.1400.1470.0120.026-0.006-0.0110.1470.0090.0520.0070.0330.0120.0210.532-0.339-0.3390.0150.119-0.030-0.0660.0610.004-0.0880.3380.1840.166-0.041-0.0480.0900.090-0.0590.1470.0610.1550.1590.0390.0310.476-0.0780.0350.0890.0670.0480.224-0.0510.2360.2390.2090.2280.1200.2280.0410.1250.9991.0000.7240.0130.9650.2450.1510.040
total_rec_int0.0200.0110.0130.1640.2420.1480.0280.147-0.0560.2300.0020.046-0.0090.0390.0460.0490.0130.0910.1170.1300.024-0.110-0.1100.7010.7000.1960.7820.0310.0180.3940.0000.6570.0290.0000.041-0.308-0.0210.042-0.0010.0480.0350.6660.390-0.072-0.0720.2580.7010.0240.2600.0870.1040.004-0.0050.123-0.056-0.021-0.067-0.0100.013-0.052-0.027-0.056-0.0070.1660.1800.1180.1280.0700.1180.1210.1790.1280.0070.0120.0050.0010.1290.0070.0770.0150.0350.0040.0170.8020.0580.058-0.0140.213-0.015-0.0470.0430.0150.0470.3330.2380.263-0.010-0.024-0.025-0.025-0.0280.0700.0360.1240.1660.0780.1520.516-0.0730.1060.2510.1680.0490.498-0.0290.1800.1650.1350.2270.1310.1370.0280.1280.7240.7241.0000.0730.5720.1610.1540.046
total_rec_late_fee0.0110.0170.0010.050-0.000-0.0150.006-0.004-0.0620.0370.0120.1540.0070.0270.0780.0510.0130.0060.0020.0070.005-0.060-0.0600.0040.0040.0210.0430.4860.0310.1510.1400.0790.0700.0000.003-0.0420.0230.0120.0160.0320.0230.0100.077-0.187-0.187-0.0800.0050.060-0.020-0.010-0.012-0.007-0.012-0.022-0.045-0.028-0.051-0.014-0.011-0.034-0.024-0.0400.027-0.012-0.004-0.026-0.0230.006-0.022-0.020-0.004-0.0120.0000.0000.0280.017-0.0120.0080.0120.0210.0170.0050.0040.040-0.041-0.041-0.0510.0340.000-0.0120.0000.0000.152-0.022-0.0290.0360.0470.079-0.129-0.1290.099-0.052-0.030-0.021-0.0110.0200.053-0.0780.1750.036-0.0950.0220.0200.0190.006-0.007-0.016-0.0120.0030.014-0.0600.0070.0100.0130.0130.0731.000-0.018-0.0520.0250.041
total_rec_prncp0.014-0.0140.0160.0170.3020.1860.1090.1890.0880.086-0.001-0.210-0.0280.0540.2560.0260.0070.173-0.032-0.0660.0280.0540.0540.5470.5450.0490.241-0.1070.0080.1590.0000.3070.0440.1620.066-0.494-0.0410.114-0.0370.0300.0080.566-0.0690.2010.2010.6340.5470.1980.2310.0920.1600.0180.0210.202-0.036-0.010-0.1040.0130.022-0.0310.003-0.042-0.0280.1290.1110.1400.2130.0750.1240.1920.1110.1280.0000.015-0.008-0.0250.1280.0000.031-0.0100.0120.0060.0120.252-0.402-0.4020.0200.077-0.031-0.0640.0550.007-0.2150.2950.1410.119-0.052-0.0570.1450.145-0.0790.1540.0790.1500.1410.020-0.0290.142-0.0760.0790.0650.0460.0410.131-0.0500.2170.2250.1970.1910.0920.2240.0310.0990.9660.9650.572-0.0181.0000.2340.1320.059
total_rev_hi_lim0.0050.1430.026-0.2890.4130.3540.0000.1860.679-0.227-0.021-0.057-0.0390.0000.023-0.0660.0090.0330.1590.1650.0130.3610.3610.4180.4190.0380.273-0.0540.0000.1190.0000.3820.0000.0000.0340.088-0.1200.023-0.0140.0250.0040.382-0.2530.2560.2560.1850.4180.0070.5620.1360.327-0.096-0.0670.254-0.0010.0600.100-0.008-0.121-0.032-0.002-0.050-0.1720.4710.4640.5890.5120.0880.6060.5250.4660.5490.0000.000-0.0830.0940.5470.0920.0670.0030.0340.1380.1810.2420.1360.1360.223-0.173-0.159-0.1500.0110.000-0.0580.7340.546-0.180-0.046-0.0680.2980.298-0.0400.1660.0480.2980.2790.032-0.1890.372-0.0210.0000.0850.036-0.0360.015-0.1260.3690.4800.4280.4060.1310.8760.0820.1600.2450.2450.161-0.0520.2341.0000.0120.013
verification_status0.0120.0690.0180.1100.0220.0540.0560.0210.0320.0980.0150.0410.0110.0270.0890.0130.0080.0320.0100.1350.0390.1230.1230.1550.1560.1780.0990.0000.0000.0420.0000.1580.1220.0580.0271.0000.0720.0840.0350.0480.0510.1520.1850.0900.0900.0740.1550.0830.0040.0210.0400.0280.0230.0290.0200.0140.0550.0130.0160.0270.0430.0160.0160.0290.0430.0240.0240.0100.0140.0230.0370.0110.0110.0080.0140.0800.0110.0510.0130.0560.0490.0570.0520.1230.0830.0830.0200.0960.0150.0210.0620.0000.0450.0160.0680.0990.0000.0000.0380.0380.0200.0240.0000.0330.0240.0000.0600.0750.0000.0000.0000.1920.0110.0950.0040.0340.0210.0270.0250.0260.0050.0270.0180.1510.1510.1540.0250.1320.0121.0000.733
verification_status_joint0.0000.0240.0000.0440.0000.0451.0000.0000.0000.0400.0000.0200.0140.0310.0000.0001.0001.0000.0470.1710.0410.0490.0490.1730.1700.0910.2450.0000.0000.0000.2670.3110.2060.0000.0291.0000.0230.0000.0280.0360.0180.1420.0970.0000.0000.0780.1730.0551.0000.0320.0540.0000.0340.0000.0710.0380.0750.0320.0390.0000.0400.0000.0000.0000.0330.0000.0050.0190.0260.0000.0420.0320.0000.0000.0000.0310.0310.0080.0270.0250.0480.0130.0000.0000.1500.1500.0000.0430.0230.0180.0440.0000.0090.0180.0720.0540.0000.0000.0270.0270.0260.0360.0000.0280.0200.0370.0680.0000.0000.0760.0000.1100.0300.0001.0000.0160.0270.0250.0360.0240.0000.0220.0310.0400.0400.0460.0410.0590.0130.7331.000

Missing values

2026-01-19T10:07:23.614032image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2026-01-19T10:07:24.528128image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2026-01-19T10:07:27.584327image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idmember_idloan_amntfunded_amntfunded_amnt_invtermint_rateinstallmentgradesub_gradeemp_titleemp_lengthhome_ownershipannual_incverification_statusissue_dloan_statuspymnt_planurldescpurposetitlezip_codeaddr_statedtidelinq_2yrsearliest_cr_linefico_range_lowfico_range_highinq_last_6mthsmths_since_last_delinqmths_since_last_recordopen_accpub_recrevol_balrevol_utiltotal_accinitial_list_statusout_prncpout_prncp_invtotal_pymnttotal_pymnt_invtotal_rec_prncptotal_rec_inttotal_rec_late_feerecoveriescollection_recovery_feelast_pymnt_dlast_pymnt_amntnext_pymnt_dlast_credit_pull_dlast_fico_range_highlast_fico_range_lowcollections_12_mths_ex_medmths_since_last_major_derogpolicy_codeapplication_typeannual_inc_jointdti_jointverification_status_jointacc_now_delinqtot_coll_amttot_cur_balopen_acc_6mopen_act_ilopen_il_12mopen_il_24mmths_since_rcnt_iltotal_bal_ilil_utilopen_rv_12mopen_rv_24mmax_bal_bcall_utiltotal_rev_hi_liminq_fitotal_cu_tlinq_last_12macc_open_past_24mthsavg_cur_balbc_open_to_buybc_utilchargeoff_within_12_mthsdelinq_amntmo_sin_old_il_acctmo_sin_old_rev_tl_opmo_sin_rcnt_rev_tl_opmo_sin_rcnt_tlmort_accmths_since_recent_bcmths_since_recent_bc_dlqmths_since_recent_inqmths_since_recent_revol_delinqnum_accts_ever_120_pdnum_actv_bc_tlnum_actv_rev_tlnum_bc_satsnum_bc_tlnum_il_tlnum_op_rev_tlnum_rev_acctsnum_rev_tl_bal_gt_0num_satsnum_tl_120dpd_2mnum_tl_30dpdnum_tl_90g_dpd_24mnum_tl_op_past_12mpct_tl_nvr_dlqpercent_bc_gt_75pub_rec_bankruptciestax_lienstot_hi_cred_limtotal_bal_ex_morttotal_bc_limittotal_il_high_credit_limitrevol_bal_jointsec_app_fico_range_lowsec_app_fico_range_highsec_app_earliest_cr_linesec_app_inq_last_6mthssec_app_mort_accsec_app_open_accsec_app_revol_utilsec_app_open_act_ilsec_app_num_rev_acctssec_app_chargeoff_within_12_mthssec_app_collections_12_mths_ex_medsec_app_mths_since_last_major_deroghardship_flaghardship_typehardship_reasonhardship_statusdeferral_termhardship_amounthardship_start_datehardship_end_datepayment_plan_start_datehardship_lengthhardship_dpdhardship_loan_statusorig_projected_additional_accrued_interesthardship_payoff_balance_amounthardship_last_payment_amountdisbursement_methoddebt_settlement_flagdebt_settlement_flag_datesettlement_statussettlement_datesettlement_amountsettlement_percentagesettlement_termdefault_flag
172394796404876None35000.035000.035000.036 months18.991282.79DD3Procurement9 yearsMORTGAGE90000.0VerifiedJan-2017Charged Offnhttps://lendingclub.com/browse/loanDetail.action?loan_id=96404876Nonedebt_consolidationDebt consolidation773xxTX26.511.0Sep-2001680.0684.00.011.0NaN8.00.011095.066.518.0f0.000.0014898.15000014898.157294.495609.560.001994.10358.9380Apr-201850.00NoneOct-2018644.0640.00.0NaN1.0IndividualNaNNaNNone0.00.0121440.00.03.01.03.011.033753.077.00.01.08336.074.017200.00.02.00.04.015180.00.0104.20.00.086.0184.020.011.04.020.0NaN16.011.00.01.04.01.04.05.04.09.04.08.00.00.00.01.094.1100.00.00.0140785.044848.08000.043735.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashNNoneNoneNoneNaNNaNNaN1
584381116270275None4000.04000.04000.036 months13.59135.92CC2NoneNoneMORTGAGE20000.0Source VerifiedAug-2017Currentnhttps://lendingclub.com/browse/loanDetail.action?loan_id=116270275Nonedebt_consolidationDebt consolidation548xxWI18.072.0Oct-2004660.0664.00.016.0NaN4.00.05997.070.612.0w2090.942090.942576.4400002576.441909.06667.380.000.000.0000Mar-2019135.92Apr-2019Mar-2019669.0665.00.040.01.0IndividualNaNNaNNone0.00.05997.00.00.00.00.0118.00.0NaN0.01.04732.071.08500.02.00.00.01.01499.02215.070.50.00.0127.0154.023.023.03.045.016.017.016.00.03.04.03.04.03.04.06.04.04.00.00.00.00.075.00.00.00.08500.05997.07500.00.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashNNoneNoneNoneNaNNaNNaN0
216926294716506None9600.09600.09600.036 months12.74322.27CC1Executive Chef5 yearsRENT72500.0VerifiedDec-2016Currentnhttps://lendingclub.com/browse/loanDetail.action?loan_id=94716506Nonedebt_consolidationDebt consolidation322xxFL20.910.0Nov-2006670.0674.00.0NaNNaN20.00.013531.029.927.0f2751.922751.928694.5000008694.506848.081846.420.000.000.0000Mar-2019322.27Apr-2019Mar-2019729.0725.00.0NaN1.0IndividualNaNNaNNone0.0293.052324.00.02.01.02.011.038793.064.00.09.04463.035.045200.00.01.00.011.02616.019439.040.60.00.0121.049.016.011.00.019.0NaN16.0NaN0.08.010.010.014.05.018.022.010.020.00.00.00.01.0100.010.00.00.090751.052324.032700.045551.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashNNoneNoneNoneNaNNaNNaN0
66991579044197None15600.015600.015600.060 months7.89315.50AA5Treasurer1 yearMORTGAGE105000.0Not VerifiedJun-2016Fully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=79044197Nonecredit_cardCredit card refinancing609xxIL16.320.0Oct-2002765.0769.00.0NaNNaN14.00.015653.039.938.0f0.000.0017039.52475617039.5215600.001439.520.000.000.0000Sep-201712629.36NoneApr-2018714.0710.00.0NaN1.0IndividualNaNNaNNone0.00.0254214.00.04.02.03.011.0100573.074.00.00.014325.054.039200.02.02.01.03.019555.012647.055.30.00.0163.0148.029.011.02.099.0NaN10.0NaN0.03.03.06.07.026.09.010.03.014.00.00.00.02.0100.00.00.00.0288451.0116226.028300.0101968.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashNNoneNoneNoneNaNNaNNaN0
224640491443780None8000.08000.08000.036 months8.99254.37BB1RN10+ yearsRENT155000.0Not VerifiedOct-2016Fully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=91443780Nonecredit_cardCredit card refinancing941xxCA2.960.0Dec-2011675.0679.01.0NaNNaN4.00.012626.063.06.0w0.000.008428.4233068428.428000.00428.420.000.000.0000Jun-201746.34NoneJun-2017664.0660.00.0NaN1.0IndividualNaNNaNNone0.00.016582.01.01.00.01.018.03956.079.01.01.07824.063.020200.00.01.01.02.04145.06733.063.00.00.047.058.05.05.00.05.0NaN5.0NaN0.03.03.03.03.03.03.03.03.04.0NaN0.00.01.0100.033.30.00.025200.016582.020200.05000.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashNNoneNoneNoneNaNNaNNaN0
195575588766045None32000.032000.031950.036 months16.991140.73DD1Special Agent10+ yearsMORTGAGE136000.0VerifiedSep-2016Charged Offnhttps://lendingclub.com/browse/loanDetail.action?loan_id=88766045Nonedebt_consolidationDebt consolidation928xxCA33.220.0Mar-1974690.0694.03.065.069.021.03.039857.053.037.0f0.000.0014821.64000014798.487320.824026.0757.043417.71615.1878Jul-20172338.50NoneJan-2018579.0575.00.065.01.0IndividualNaNNaNNone0.00.0189691.04.05.03.03.04.0149834.093.02.03.015213.072.075200.02.07.012.06.09485.022806.055.00.00.0150.0510.01.01.02.01.0NaN4.0NaN2.05.09.09.014.011.016.024.09.021.00.00.00.05.0100.022.21.02.0247974.0189691.050700.0172774.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashNNoneNoneNoneNaNNaNNaN1
1552438131832227None35000.035000.035000.036 months14.071197.41CC3NoneNoneMORTGAGE50000.0Source VerifiedMay-2018Currentnhttps://lendingclub.com/browse/loanDetail.action?loan_id=131832227Nonedebt_consolidationDebt consolidation945xxCA54.320.0Nov-2005675.0679.01.049.0NaN8.00.03182.044.224.0w26701.1426701.1411919.38000011919.388298.863620.520.000.000.0000Mar-20191197.41Apr-2019Mar-2019674.0670.00.0NaN1.0Joint App150000.026.95Source Verified0.00.0490998.03.03.02.04.06.098379.095.01.01.01357.075.07200.04.02.05.07.061375.03851.030.00.00.0149.0129.01.01.02.01.049.01.049.00.02.03.02.07.011.03.011.03.08.00.00.00.05.087.550.00.00.0512302.0101561.05500.0115665.029529.0695.0699.0Oct-20040.02.013.063.55.013.00.00.0NaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashNNoneNoneNoneNaNNaNNaN0
854994136649827None16000.016000.016000.036 months11.06524.28BB3Vice President2 yearsRENT51000.0Source VerifiedJul-2018Currentnhttps://lendingclub.com/browse/loanDetail.action?loan_id=136649827Nonedebt_consolidationDebt consolidation141xxNY24.960.0Oct-2010680.0684.00.0NaNNaN8.00.015622.051.48.0w12886.4412886.444184.4100004184.413113.561070.850.000.000.0000Mar-2019524.28Apr-2019Mar-2019619.0615.00.0NaN1.0IndividualNaNNaNNone0.00.055204.01.02.00.01.015.039582.082.03.04.06628.070.030400.01.00.00.05.06901.013403.052.80.00.093.047.06.06.00.06.0NaN15.0NaN0.04.05.05.05.02.06.06.05.08.00.00.00.03.0100.040.00.00.078906.055204.028400.048506.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNDirectPayNNoneNoneNoneNaNNaNNaN0
199217286985198None24000.024000.024000.060 months16.99596.34DD1RN2 yearsMORTGAGE110000.0Not VerifiedAug-2016Charged Offnhttps://lendingclub.com/browse/loanDetail.action?loan_id=86985198Nonedebt_consolidationDebt consolidation809xxCO15.080.0Apr-2004680.0684.01.0NaNNaN29.00.024669.081.748.0w0.000.0011990.63000011990.635540.325890.6759.64500.0090.0000Aug-201850.00NoneMar-2019584.0580.00.0NaN1.0IndividualNaNNaNNone0.00.0474565.02.024.01.02.011.0164960.0103.01.03.015919.099.030200.02.01.06.06.016949.0981.094.20.00.0130.0148.04.04.01.021.0NaN4.0NaN0.01.03.01.07.026.04.021.03.029.00.00.00.03.0100.0100.00.00.0477076.0189629.016900.0160726.0NaNNaNNaNNoneNaNNaNNaNNaNNaNNaNNaNNaNNaNNNoneNoneNoneNaNNaNNoneNoneNoneNaNNaNNoneNaNNaNNaNCashYJun-2018ACTIVEJun-20189641.050.018.01
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